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Co-endemicity of Pulmonary Tuberculosis and Intestinal Helminth Infection in the People's Republic of China.

Li XX, Ren ZP, Wang LX, Zhang H, Jiang SW, Chen JX, Wang JF, Zhou XN - PLoS Negl Trop Dis (2016)

Bottom Line: There are co-endemic, high prevalence areas of both diseases, whose delimitation is essential for devising effective control strategies.Our results indicate that gross domestic product (GDP) per capita had a negative association, while rural regions, the arid and polar zones and elevation had positive association with active PTB prevalence; for the IHI prevalence, GDP per capita and distance to water bodies had a negative association, the equatorial and warm zones and the normalized difference vegetation index had a positive association.Thus, co-endemic areas of active PTB and IHI were located in the south-western regions of China, which might be determined by socio-economic factors, such as GDP per capita.

View Article: PubMed Central - PubMed

Affiliation: National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, People's Republic of China.

ABSTRACT
Both pulmonary tuberculosis (PTB) and intestinal helminth infection (IHI) affect millions of individuals every year in China. However, the national-scale estimation of prevalence predictors and prevalence maps for these diseases, as well as co-endemic relative risk (RR) maps of both diseases' prevalence are not well developed. There are co-endemic, high prevalence areas of both diseases, whose delimitation is essential for devising effective control strategies. Bayesian geostatistical logistic regression models including socio-economic, climatic, geographical and environmental predictors were fitted separately for active PTB and IHI based on data from the national surveys for PTB and major human parasitic diseases that were completed in 2010 and 2004, respectively. Prevalence maps and co-endemic RR maps were constructed for both diseases by means of Bayesian Kriging model and Bayesian shared component model capable of appraising the fraction of variance of spatial RRs shared by both diseases, and those specific for each one, under an assumption that there are unobserved covariates common to both diseases. Our results indicate that gross domestic product (GDP) per capita had a negative association, while rural regions, the arid and polar zones and elevation had positive association with active PTB prevalence; for the IHI prevalence, GDP per capita and distance to water bodies had a negative association, the equatorial and warm zones and the normalized difference vegetation index had a positive association. Moderate to high prevalence of active PTB and low prevalence of IHI were predicted in western regions, low to moderate prevalence of active PTB and low prevalence of IHI were predicted in north-central regions and the southeast coastal regions, and moderate to high prevalence of active PTB and high prevalence of IHI were predicted in the south-western regions. Thus, co-endemic areas of active PTB and IHI were located in the south-western regions of China, which might be determined by socio-economic factors, such as GDP per capita.

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Spatial distributions of covariates across P. R. China (A. gross domestic product [GDP] per capita; B. population density; C. urban extents; D. climate zones; E. precipitation; F. air temperature; G. land surface temperature for day; H. land surface temperature for night; I. elevation; J. water bodies; K. vertical columnar density [VCD] of nitrogen dioxide [NO2]; L. VCD of sulfur dioxide [SO2]; M. concentration of particulate matter of 2.5 micrometers [PM2.5]; N. soil moisture; O. normalized difference vegetation index [NDVI]).
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pntd.0004580.g002: Spatial distributions of covariates across P. R. China (A. gross domestic product [GDP] per capita; B. population density; C. urban extents; D. climate zones; E. precipitation; F. air temperature; G. land surface temperature for day; H. land surface temperature for night; I. elevation; J. water bodies; K. vertical columnar density [VCD] of nitrogen dioxide [NO2]; L. VCD of sulfur dioxide [SO2]; M. concentration of particulate matter of 2.5 micrometers [PM2.5]; N. soil moisture; O. normalized difference vegetation index [NDVI]).

Mentions: Proxies of socio-economic, climatic, geographical and environmental factors were extracted as covariates from different readily accessible sources, as shown in Tables 1 and 2. The gross domestic product (GDP) per capita, population density and urban extents with a binary indicator of urban/rural extent were included in the analysis to capture influences of social developments and human activities on both diseases[8,10–13]. Climate zones consisting of equatorial, arid, warm, snow and polar zones, precipitation, air temperature and land surface temperature (LST) for day and night were used to reflect impacts of climatic factors on both diseases[8,10,11,14–20], among which air temperature was only included in the analysis of active PTB[19], and LST only in the analysis of IHI[8,11,14–16,18]. Elevation and water bodies were applied to the evaluation of relationships between geographical factors and both diseases[8–11,14–18], among which Euclidean distances from survey sites to water bodies were only included in the analysis of IHI[8,11,14–16]. Vertical columnar density (VCD) of nitrogen dioxide (NO2), VCD of sulfur dioxide (SO2), concentration of particulate matter of 2.5 micrometers (PM2.5), soil moisture and normalized difference vegetation index (NDVI) were used to assess influences of environmental factors on both diseases[8,10,11,14,15,17–19,21,22], among which VCD of NO2, VCD of SO2 and PM2.5 concentration were only included in the analysis of active PTB[19,21,22], and soil moisture and NDVI only in the analysis of IHI[8,10,11,14,15,17,18]. GDP per capita and population density were obtained from the Chinese annual, full-text database, and other data were downloaded from websites providing free geospatial data products. All of the collected covariates for more than one year were averaged. Maps of all covariates can be seen in Fig 2.


Co-endemicity of Pulmonary Tuberculosis and Intestinal Helminth Infection in the People's Republic of China.

Li XX, Ren ZP, Wang LX, Zhang H, Jiang SW, Chen JX, Wang JF, Zhou XN - PLoS Negl Trop Dis (2016)

Spatial distributions of covariates across P. R. China (A. gross domestic product [GDP] per capita; B. population density; C. urban extents; D. climate zones; E. precipitation; F. air temperature; G. land surface temperature for day; H. land surface temperature for night; I. elevation; J. water bodies; K. vertical columnar density [VCD] of nitrogen dioxide [NO2]; L. VCD of sulfur dioxide [SO2]; M. concentration of particulate matter of 2.5 micrometers [PM2.5]; N. soil moisture; O. normalized difference vegetation index [NDVI]).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4835095&req=5

pntd.0004580.g002: Spatial distributions of covariates across P. R. China (A. gross domestic product [GDP] per capita; B. population density; C. urban extents; D. climate zones; E. precipitation; F. air temperature; G. land surface temperature for day; H. land surface temperature for night; I. elevation; J. water bodies; K. vertical columnar density [VCD] of nitrogen dioxide [NO2]; L. VCD of sulfur dioxide [SO2]; M. concentration of particulate matter of 2.5 micrometers [PM2.5]; N. soil moisture; O. normalized difference vegetation index [NDVI]).
Mentions: Proxies of socio-economic, climatic, geographical and environmental factors were extracted as covariates from different readily accessible sources, as shown in Tables 1 and 2. The gross domestic product (GDP) per capita, population density and urban extents with a binary indicator of urban/rural extent were included in the analysis to capture influences of social developments and human activities on both diseases[8,10–13]. Climate zones consisting of equatorial, arid, warm, snow and polar zones, precipitation, air temperature and land surface temperature (LST) for day and night were used to reflect impacts of climatic factors on both diseases[8,10,11,14–20], among which air temperature was only included in the analysis of active PTB[19], and LST only in the analysis of IHI[8,11,14–16,18]. Elevation and water bodies were applied to the evaluation of relationships between geographical factors and both diseases[8–11,14–18], among which Euclidean distances from survey sites to water bodies were only included in the analysis of IHI[8,11,14–16]. Vertical columnar density (VCD) of nitrogen dioxide (NO2), VCD of sulfur dioxide (SO2), concentration of particulate matter of 2.5 micrometers (PM2.5), soil moisture and normalized difference vegetation index (NDVI) were used to assess influences of environmental factors on both diseases[8,10,11,14,15,17–19,21,22], among which VCD of NO2, VCD of SO2 and PM2.5 concentration were only included in the analysis of active PTB[19,21,22], and soil moisture and NDVI only in the analysis of IHI[8,10,11,14,15,17,18]. GDP per capita and population density were obtained from the Chinese annual, full-text database, and other data were downloaded from websites providing free geospatial data products. All of the collected covariates for more than one year were averaged. Maps of all covariates can be seen in Fig 2.

Bottom Line: There are co-endemic, high prevalence areas of both diseases, whose delimitation is essential for devising effective control strategies.Our results indicate that gross domestic product (GDP) per capita had a negative association, while rural regions, the arid and polar zones and elevation had positive association with active PTB prevalence; for the IHI prevalence, GDP per capita and distance to water bodies had a negative association, the equatorial and warm zones and the normalized difference vegetation index had a positive association.Thus, co-endemic areas of active PTB and IHI were located in the south-western regions of China, which might be determined by socio-economic factors, such as GDP per capita.

View Article: PubMed Central - PubMed

Affiliation: National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, People's Republic of China.

ABSTRACT
Both pulmonary tuberculosis (PTB) and intestinal helminth infection (IHI) affect millions of individuals every year in China. However, the national-scale estimation of prevalence predictors and prevalence maps for these diseases, as well as co-endemic relative risk (RR) maps of both diseases' prevalence are not well developed. There are co-endemic, high prevalence areas of both diseases, whose delimitation is essential for devising effective control strategies. Bayesian geostatistical logistic regression models including socio-economic, climatic, geographical and environmental predictors were fitted separately for active PTB and IHI based on data from the national surveys for PTB and major human parasitic diseases that were completed in 2010 and 2004, respectively. Prevalence maps and co-endemic RR maps were constructed for both diseases by means of Bayesian Kriging model and Bayesian shared component model capable of appraising the fraction of variance of spatial RRs shared by both diseases, and those specific for each one, under an assumption that there are unobserved covariates common to both diseases. Our results indicate that gross domestic product (GDP) per capita had a negative association, while rural regions, the arid and polar zones and elevation had positive association with active PTB prevalence; for the IHI prevalence, GDP per capita and distance to water bodies had a negative association, the equatorial and warm zones and the normalized difference vegetation index had a positive association. Moderate to high prevalence of active PTB and low prevalence of IHI were predicted in western regions, low to moderate prevalence of active PTB and low prevalence of IHI were predicted in north-central regions and the southeast coastal regions, and moderate to high prevalence of active PTB and high prevalence of IHI were predicted in the south-western regions. Thus, co-endemic areas of active PTB and IHI were located in the south-western regions of China, which might be determined by socio-economic factors, such as GDP per capita.

Show MeSH
Related in: MedlinePlus