Temporal and Spatial Analysis of Neural Tube Defects and Detection of Geographical Factors in Shanxi Province, China

PLOS_ONEPLOS ONE, Published 21 April 2016

By Yilan Liao, Yan Zhang, Lei He, Jinfeng Wang, Xin Liu, Ningxu Zhang, and Bing Xu

Background: Neural tube defects (NTDs) are congenital birth defects that occur in the central nervous system, and they have the highest incidence among all birth defects. Shanxi Province in China has the world’s highest rate of NTDs. Since the 1990s, China’s government has worked on many birth defect prevention programs to reduce the occurrence of NTDs, such as pregnancy planning, health education, genetic counseling, antenatal ultrasonography and serological screening. However, the rate of NTDs in Shanxi Province is still higher than the world’s average morbidity rate after intervention. In addition, Shanxi Province has abundant coal reserves, and is the largest coal production province in China. The objectives of this study are to determine the temporal and spatial variation of the NTD rate in rural areas of Shanxi Province, China, and identify geographical environmental factors that were associated with NTDs in the risk area.

Methods: In this study, Heshun County and Yuanping County in Shanxi Province, which have high incidence of NTDs, were selected as the study areas. Two paired sample T test was used to analyze the changes in the risk of NTDs from the time dimension. Ripley’s k function and spatial filtering were combined with geographic information system (GIS) software to study the changes in the risk of NTDs from the spatial dimension. In addition, geographical detectors were used to identify the risk geographical environmental factors of NTDs in the study areas, especially the areas close to the coal sites and main roads.

Cluster areas of Neural Tube Defects in Heshun County and Yuanping County.

Cluster areas of Neural Tube Defects in Heshun County and Yuanping County.

Results: In both Heshun County and Yuanping County, the incidence of NTDs was significantly (P<0.05) reduced after intervention. The results from spatial analysis showed that significant spatial heterogeneity existed in both counties. NTD clusters were still identified in areas close to coal sites and main roads after interventions. This study also revealed that the elevation, fault and soil types always had a larger influence on the incidence of NTDs in our study areas. In addition, distance to the river was a risk factor of NTDs in areas close to the coal sites and main roads.

Conclusion: The existing interventions may have played an important role to reduce the incidence of NTDs. However, there is still spatial heterogeneity in both counties after using the traditional intervention methods. The government needs to take more measures to strengthen the environmental restoration to prevent the occurrence of NTDs, especially those areas close to coal sites and main roads. The outcome of this research provides an important theoretical basis and technical support for the government to prevent the occurrence of NTDs.”

Risks of developing breast and colorectal cancer in association with incomes and geographic locations in Texas: a retrospective cohort study

bmc cancerBMC Cancer 2016 16:294, Published 26 April 2016

By Zheyu Liu, Kai Zhang, and Xianglin L. Du

Background: No study has been conducted to investigate the spatial pattern and association of socioeconomic status (such as income) with breast and colorectal cancer incidence in Texas, United States. This study aimed to determine whether median household income was associated with the risk of developing breast and colorectal cancer in Texas and to identify higher cancer risks by race/ethnicity and geographic areas.

Methods:This was a retrospective cohort study with an ecological component in using aggregated measures at the county level. We identified 243,677 women with breast cancer and 155,534 men and women with colorectal cancer residing in 254 counties in Texas in 1995–2011 from the public-use dataset of Texas Cancer Registry. The denominator population and median household income at the county level was obtained from the U.S. Bureau of the Census. Cancer incidence rates were calculated as number of cases per 100,000 persons and age-adjusted using the 2000 US population data. We used the ArcGIS v10.1 (geographic information system software) to identify multiple clustered counties with high and low cancer incidences in Texas.

Geographic variations of colorectal cancer incidence adjusted for age and median household income in Texas, 1995–2011

Geographic variations of colorectal cancer incidence adjusted for age and median household income in Texas, 1995–2011

Results: Age-adjusted breast cancer incidence rate in the highest median income quintile group was 151.51 cases per 100,000 in 2008–2011 as compared to 98.95 cases per 100,000 in the lowest median income quintile group. The risk of colorectal cancer appeared to decrease with increasing median income in racial/ethnic population. Spatial analysis revealed the significant low breast cancer incidence cluster regions located in southwest US-Mexico border counties in Texas.

Conclusions: This study demonstrated that higher income was associated with an increased risk of breast cancer and a decreased risk of colorectal cancer in Texas. There were geographic variations with cancer incidence clustered in high risk areas in Texas. Future studies may need to explore more factors that might explain income and cancer risk associations and their geographic variations.”

Recent improvement and projected worsening of weather in the United States

natureNature, 532, 357–360, Published online 20 April 2016

By Patrick J. Egan and Megan Mullin

“As climate change unfolds, weather systems in the United States have been shifting in patterns that vary across regions and seasons. Climate science research typically assesses these changes by examining individual weather indicators, such as temperature or precipitation, in isolation, and averaging their values across the spatial surface. As a result, little is known about population exposure to changes in weather and how people experience and evaluate these changes considered together. Here we show that in the United States from 1974 to 2013, the weather conditions experienced by the vast majority of the population improved.

Population growth rate equivalent change in WPI by decade, derived from county-by-county regressions of annual WPI on year

Population growth rate equivalent change in WPI by decade, derived from county-by-county regressions of annual WPI on year

“Using previous research on how weather affects local population growth to develop an index of people’s weather preferences, we find that 80% of Americans live in counties that are experiencing more pleasant weather than they did four decades ago. Virtually all Americans are now experiencing the much milder winters that they typically prefer, and these mild winters have not been offset by markedly more uncomfortable summers or other negative changes. Climate change models predict that this trend is temporary, however, because US summers will eventually warm more than winters. Under a scenario in which greenhouse gas emissions proceed at an unabated rate (Representative Concentration Pathway 8.5), we estimate that 88% of the US public will experience weather at the end of the century that is less preferable than weather in the recent past. Our results have implications for the public’s understanding of the climate change problem, which is shaped in part by experiences with local weather. Whereas weather patterns in recent decades have served as a poor source of motivation for Americans to demand a policy response to climate change, public concern may rise once people’s everyday experiences of climate change effects start to become less pleasant.”

Geostatistical interpolation model selection based on ArcGIS and spatio-temporal variability analysis of groundwater level in piedmont plains, northwest China

SpringerPlus, Published 11 April 2016

By Yong Xiao, Xiaomin Gu, Shiyang YinEmail author, Jingli Shao, Yali Cui, Qiulan Zhang, and Yong Niu

“Based on the geo-statistical theory and ArcGIS geo-statistical module, datas of 30 groundwater level observation wells were used to estimate the decline of groundwater level in Beijing piedmont. Seven different interpolation methods (inverse distance weighted interpolation, global polynomial interpolation, local polynomial interpolation, tension spline interpolation, ordinary Kriging interpolation, simple Kriging interpolation and universal Kriging interpolation) were used for interpolating groundwater level between 2001 and 2013. Cross-validation, absolute error and coefficient of determination (R2) was applied to evaluate the accuracy of different methods.

Groundwater level drawdown during 2001 and 2013.

Groundwater level drawdown during 2001 and 2013.

“The result shows that simple Kriging method gave the best fit. The analysis of spatial and temporal variability suggest that the nugget effects from 2001 to 2013 were increasing, which means the spatial correlation weakened gradually under the influence of human activities. The spatial variability in the middle areas of the alluvial–proluvial fan is relatively higher than area in top and bottom. Since the changes of the land use, groundwater level also has a temporal variation, the average decline rate of groundwater level between 2007 and 2013 increases compared with 2001–2006. Urban development and population growth cause over-exploitation of residential and industrial areas. The decline rate of the groundwater level in residential, industrial and river areas is relatively high, while the decreasing of farmland area and development of water-saving irrigation reduce the quantity of water using by agriculture and decline rate of groundwater level in agricultural area is not significant.”

Polar Challenge: Creating an Autonomous Underwater Vehicle for Under Sea-Ice Exploration

World Ocean CouncilWorld Ocean Council Partners with World Climate Research Programme and Prince Albert II of Monaco Foundation to Promote Industry Involvement in Polar Research Innovation

The World Ocean Council (WOC) is working to foster private sector participation in the Polar Challenge – a competition to develop an Autonomous Underwater Vehicle (AUV) capable of a 2,000 km mission under the sea-ice in the Arctic or Antarctic, with a prize of 500,000 Swiss francs to the winner.

The World Climate Research Programme (WCRP) and Prince Albert II of Monaco Foundation hope the competition will stimulate innovation towards a cost-effective, autonomous and scalable observing network for ice-covered ocean regions.

“With the Polar Challenge, we hope to open new horizons in under-ice navigation,
endurance and environmental monitoring that is vital to understanding polar oceans,” said WCRP Director David Carlson.

“The reliability of long-term climate change outlooks in polar regions is severely limited by the scarcity and cost of observations of the sea-ice and below,” emphasized WCRP Senior Scientist Michel Rixen. “New generation AUVs such as underwater gliders provide a potential cost-effective option for scaling up observing networks for the Polar regions,” added Mr Rixen.

WOC CEO, Paul Holthus, noted that, “The use of AUVs and other intensive data collection technology can be cost-effectively augmented by harnessing the use of commercial vessels for data collection as they operate in polar waters, and we are working to advance this through the WOC ‘Smart Ocean-Smart Industries’ program.”

Currently AUVs are primarily used in ice-free zones, where they can surface to get a GPS fix and transmit data, e.g. temperature, salinity, chlorophyll and acidity. But under the sea-ice, the operating range, positioning and data transmission are a major challenge. Progress on power systems, navigation and communication create the potential to expand the scope of AUVs to under sea-ice operations. The Polar Challenge advances WCRP research priorities in polar oceans and will contribute to the World Meteorological Organization (WMO) polar initiatives that benefit the wider community (weather, ocean, environment, safety, transport, energy, tourism, etc).

The WCRP invites contributions from all relevant stakeholders and provides more details, including competition rules and registration, at: www.wcrp-climate.org/polarchallenge.

The Polar Challenge was announced last week at the Arctic Observing Summit (AOS), in Fairbanks, Alaska. WOC co-organized the private sector theme sessions of the Arctic Observing Summit, which addressed industry experience in, and needs for, Arctic observations and data, and culminated in a workshop on fostering data collection and sharing by industry.

The AOS brought together 450 delegates from 30 countries – representing industry, science, indigenous peoples, government agencies, and NGOs. The AOS 2016 Conference Statement outlines seven major recommendations for developing a pathway towards an internationally supported, pan-Arctic observing system. Click here for the AOS Statement.

Life History Traits and Niche Instability Impact Accuracy and Temporal Transferability for Historically Calibrated Distribution Models of North American Birds

PLOS_ONEPLOS | One, Published 09 March 2016

By Guinevere O. U. Wogan

“A primary assumption of environmental niche models (ENMs) is that models are both accurate and transferable across geography or time; however, recent work has shown that models may be accurate but not highly transferable. While some of this is due to modeling technique, individual species ecologies may also underlie this phenomenon. Life history traits certainly influence the accuracy of predictive ENMs, but their impact on model transferability is less understood. This study investigated how life history traits influence the predictive accuracy and transferability of ENMs using historically calibrated models for birds.

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“In this study I used historical occurrence and climate data (1950-1990s) to build models for a sample of birds, and then projected them forward to the ‘future’ (1960-1990s). The models were then validated against models generated from occurrence data at that ‘future’ time. Internal and external validation metrics, as well as metrics assessing transferability, and Generalized Linear Models were used to identify life history traits that were significant predictors of accuracy and transferability. This study found that the predictive ability of ENMs differs with regard to life history characteristics such as range, migration, and habitat, and that the rarity versus commonness of a species affects the predicted stability and overlap and hence the transferability of projected models. Projected ENMs with both high accuracy and transferability scores, still sometimes suffered from over- or under- predicted species ranges. Life history traits certainly influenced the accuracy of predictive ENMs for birds, but while aspects of geographic range impact model transferability, the mechanisms underlying this are less understood.”

Spatial analysis of visceral leishmaniasis in the oases of the plains of Kashi Prefecture, Xinjiang Uygur Autonomous Region, China

pvParasites & Vectors, 2016, 9:148, Published 15 March 2016

By Li-ying Wang, Wei-ping Wu, Qing Fu, Ya-yi Guan, Shuai Han, Yan-lin Niu, Su-xiang Tong, Israyil Osman, Song Zhang, and Kaisar Kaisar
Background: Kashi Prefecture of Xinjiang is one of the most seriously affected areas with anthroponotic visceral leishmaniasis in China. A better understanding of space distribution features in this area was needed to guide strategies to eliminate visceral leishmaniasis from highly endemic areas. We performed a spatial analysis using the data collected in Bosh Klum Township in Xinjiang China.

Methods: Based on the report of endemic diseases between 1990 and 2005, three villages with a high number of visceral leishmaniasis cases in Bosh Klum Township were selected. We conducted a household survey to collect the baseline data of kala-azar patients using standard case definitions. The geographical information was recorded with GIS equipment. A binomial distribution fitting test, runs test, and Scan statistical analysis were used to assess the space distribution of the study area.

13071_2016_1430_Fig2_HTML.gif

Results: The result of the binomial distribution fitting test showed that the distribution of visceral leishmaniasis cases in local families was inconsistent (χ2 = 53.23, P < 0.01). The results of runs test showed that the distribution of leishmaniasis infected families along the channel was not random in the group of more than five infected families. The proportion of this kind of group in all infected families was 63.84 % (113 of 177). In the Scan statistical analysis, spatial aggregation was analyzed by poisson model, which found 3 spatial distribution areas 1) Zone A was located in a center point of 76.153447°E, 39.528477°N within its 1.11 mile radius, where the cumulative life-incidence of leishmaniasis was 1.95 times as high as that in surrounding areas (P < 0.05); 2) Zone B was located in a center point of 76.111968°E, 39.531895°N within its 0.54 mile radius, where the cumulative life-incidence of leishmaniasis was 1.82 times as high as that in surrounding areas (P < 0.01); and 3) Zone C was located in a center point of 76.195427°E, 39.563835°N within its 0.68 mile radius, where the cumulative life-incidence of leishmaniasis was 1.31 times as high as that in surrounding areas (P < 0.05).

Conclusions: The spatial distribution of visceral leishmaniasis-infected families was clustered. Thus, the proper use of this finding would be an improvement in highly endemic areas, which could help identify the types of endemic areas and population at high risk and carry out appropriate measures to prevent and control VL in this area as well.”