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Spatio-temporal distribution of human lifespan in China.

Wang S, Luo K, Liu Y - Sci Rep (2015)

Bottom Line: The spatial autocorrelation analyses indicate less spatial dependency and several discontinuous clusters regions of high-CH and LI areas.The factors of temperature, topography and wet/dry climate lack of significant influence on CH and LI.It can be inferred that, in addition to genetic factor and living custom, some unique and long-term environmental effects may be related with high or low values of CH and LI.

View Article: PubMed Central - PubMed

Affiliation: Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.

ABSTRACT
Based on the data of latest three Chinese population censuses (1990-2010), four lifespan indicators were calculated: centenarians per one hundred thousand inhabitants (CH); longevity index (LI); the percentage of the population aged at least 80 years (ultra-octogenarian index, UOI) and life expectancy at birth (LEB). The spatio-temporal distributions of data at Chinese county level show that high-longevity areas (high values of CH and LI) and low-longevity areas (low CH and LI values) both exhibit clear non-uniformity of spatial distribution and relative immobility through time. Contrarily, the distribution of UOI and LEB shows a decline from the east to the west. The spatial autocorrelation analyses indicate less spatial dependency and several discontinuous clusters regions of high-CH and LI areas. The factors of temperature, topography and wet/dry climate lack of significant influence on CH and LI. It can be inferred that, in addition to genetic factor and living custom, some unique and long-term environmental effects may be related with high or low values of CH and LI.

No MeSH data available.


Map of local spatial autocorrelation of lifespan indicators (UOI, LI and CH) in China in 1990, 2000 and 2010.The maps show significant areas with p < 0.05 as red, blue, purple and yellow, and no significant areas as grey. High-high (HH) and low-low (LL) = spatial clusters; High-low (HL) and low-high (LH) = spatial outliers. The maps were created using Arc GIS Geographic Information Systems software version 10.0 (Environmental Systems Research Institute Inc, Redlands, Calif).
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f4: Map of local spatial autocorrelation of lifespan indicators (UOI, LI and CH) in China in 1990, 2000 and 2010.The maps show significant areas with p < 0.05 as red, blue, purple and yellow, and no significant areas as grey. High-high (HH) and low-low (LL) = spatial clusters; High-low (HL) and low-high (LH) = spatial outliers. The maps were created using Arc GIS Geographic Information Systems software version 10.0 (Environmental Systems Research Institute Inc, Redlands, Calif).

Mentions: Figure 4 shows the areas with significant locations color-coded by different types of spatial autocorrelation (Local Moran’s I) of four lifespan indicators, respectively. HH districts of UOI are mostly located in eastern coastal areas and inland Sichuan, Chongqing and western Hubei Provinces, whereas LL districts are mainly in northwestern China, Tibet, Inner Mongolia and Shanxi Provinces (Fig 4). The HH and LL areas of LI are smaller than UOI, whereas the south Xinjiang Autonomous Region is recognized as HH districts (Fig 4). HH districts of CH are composed by four obvious clusters: south China area (Guangxi, Guangdong and Hainan Provinces), Sichuan Basin, Huanghuai district and southern Xinjiang Autonomous Region, which is consistent with the four regions with high-centenarian-ratio mentioned above. Whereas the LL districts of CH exhibit an obvious cluster area with relative immobility through time as well, which includes Shanxi, Shaanxi, Gansu and Inner Mongolia Provinces (Fig 4). Furthermore, LEB at country level in 2010 shows much smaller HH districts than other indexes (Fig 4), which can be explained by the scattering distribution of cities with high LEB values among more counties with lower LEB level.


Spatio-temporal distribution of human lifespan in China.

Wang S, Luo K, Liu Y - Sci Rep (2015)

Map of local spatial autocorrelation of lifespan indicators (UOI, LI and CH) in China in 1990, 2000 and 2010.The maps show significant areas with p < 0.05 as red, blue, purple and yellow, and no significant areas as grey. High-high (HH) and low-low (LL) = spatial clusters; High-low (HL) and low-high (LH) = spatial outliers. The maps were created using Arc GIS Geographic Information Systems software version 10.0 (Environmental Systems Research Institute Inc, Redlands, Calif).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4561879&req=5

f4: Map of local spatial autocorrelation of lifespan indicators (UOI, LI and CH) in China in 1990, 2000 and 2010.The maps show significant areas with p < 0.05 as red, blue, purple and yellow, and no significant areas as grey. High-high (HH) and low-low (LL) = spatial clusters; High-low (HL) and low-high (LH) = spatial outliers. The maps were created using Arc GIS Geographic Information Systems software version 10.0 (Environmental Systems Research Institute Inc, Redlands, Calif).
Mentions: Figure 4 shows the areas with significant locations color-coded by different types of spatial autocorrelation (Local Moran’s I) of four lifespan indicators, respectively. HH districts of UOI are mostly located in eastern coastal areas and inland Sichuan, Chongqing and western Hubei Provinces, whereas LL districts are mainly in northwestern China, Tibet, Inner Mongolia and Shanxi Provinces (Fig 4). The HH and LL areas of LI are smaller than UOI, whereas the south Xinjiang Autonomous Region is recognized as HH districts (Fig 4). HH districts of CH are composed by four obvious clusters: south China area (Guangxi, Guangdong and Hainan Provinces), Sichuan Basin, Huanghuai district and southern Xinjiang Autonomous Region, which is consistent with the four regions with high-centenarian-ratio mentioned above. Whereas the LL districts of CH exhibit an obvious cluster area with relative immobility through time as well, which includes Shanxi, Shaanxi, Gansu and Inner Mongolia Provinces (Fig 4). Furthermore, LEB at country level in 2010 shows much smaller HH districts than other indexes (Fig 4), which can be explained by the scattering distribution of cities with high LEB values among more counties with lower LEB level.

Bottom Line: The spatial autocorrelation analyses indicate less spatial dependency and several discontinuous clusters regions of high-CH and LI areas.The factors of temperature, topography and wet/dry climate lack of significant influence on CH and LI.It can be inferred that, in addition to genetic factor and living custom, some unique and long-term environmental effects may be related with high or low values of CH and LI.

View Article: PubMed Central - PubMed

Affiliation: Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.

ABSTRACT
Based on the data of latest three Chinese population censuses (1990-2010), four lifespan indicators were calculated: centenarians per one hundred thousand inhabitants (CH); longevity index (LI); the percentage of the population aged at least 80 years (ultra-octogenarian index, UOI) and life expectancy at birth (LEB). The spatio-temporal distributions of data at Chinese county level show that high-longevity areas (high values of CH and LI) and low-longevity areas (low CH and LI values) both exhibit clear non-uniformity of spatial distribution and relative immobility through time. Contrarily, the distribution of UOI and LEB shows a decline from the east to the west. The spatial autocorrelation analyses indicate less spatial dependency and several discontinuous clusters regions of high-CH and LI areas. The factors of temperature, topography and wet/dry climate lack of significant influence on CH and LI. It can be inferred that, in addition to genetic factor and living custom, some unique and long-term environmental effects may be related with high or low values of CH and LI.

No MeSH data available.