Cyanobacteria blooms and non-alcoholic liver disease: evidence from a county level ecological study in the United States.

Feng Zhang, Jiyoung Lee, Song Liang, C K Shum
Author Information
  1. Feng Zhang: Environmental Science Graduate Program, The Ohio State University, Columbus, OH, USA. amberpku@gmail.com.
  2. Jiyoung Lee: Environmental Science Graduate Program, The Ohio State University, Columbus, OH, USA. lee.3598@osu.edu.
  3. Song Liang: Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, FL, 32610, USA. songliang@epi.ufl.edu.
  4. C K Shum: Division of Geodetic Science, School of Earth Sciences, The Ohio State University, Columbus, OH, USA. shum.3@osu.edu.

Abstract

BACKGROUND: Harmful cyanobacterial blooms present a global threat to human health. There is evidence suggesting that cyanobacterial toxins can cause liver damage and cancer. However, because there is little epidemiologic research on the effects of these toxins in humans, the excess risk of liver disease remains uncertain. The purpose of this study is to estimate the spatial distribution of cyanobacterial blooms in the United States and to conduct a Bayesian statistical analysis to test the hypothesis that contamination from cyanobacterial blooms is a potential risk factor for non-alcoholic liver disease.
METHODS: An ecological study design was employed, in which county-specific gender and age standardized mortality rates (SMR) of non-alcoholic liver disease in the United States were computed between 1999 and 2010. Bloom coverage maps were produced based on estimated phycocyanin levels from MERIS (Medium Resolution Imaging Spectrometer) water color imageries from 08/01/2005 to 09/30/2005. A scan statistical tool was used to identify significant clusters of death from non-alcoholic liver disease. A map of local indicator of spatial association (LISA) clusters and a Bayesian spatial regression model were used to analyze the relationship between cyanobacterial bloom coverage and death from non-alcoholic liver disease.
RESULTS: cyanobacterial blooms were found to be widely spread in the United States, including coastal areas; 62% of the counties (1949 out of 3109) showed signs of cyanobacterial blooms measured with MERIS. Significant clusters of deaths attributable to non-alcoholic liver disease were identified in the coastal areas impacted by cyanobacterial blooms. Bayesian regression analysis showed that bloom coverage was significantly related to the risk of non-alcoholic liver disease death. The risk from non-alcoholic liver disease increased by 0.3% (95% CI, 0.1% to 0.5%) with each 1% increase in bloom coverage in the affected county after adjusting for age, gender, educational level, and race.
CONCLUSIONS: At the population level, there is a statistically significant association between cyanobacterial blooms and non-alcoholic liver disease in the contiguous United States. Remote sensing-based water monitoring provides a useful tool for assessing health hazards, but additional studies are needed to establish a specific association between cyanobacterial blooms and liver disease.

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MeSH Term

Adolescent
Adult
Aged
Aged, 80 and over
Bacterial Toxins
Child
Child, Preschool
Cyanobacteria
Cyanobacteria Toxins
Environmental Exposure
Environmental Monitoring
Eutrophication
Female
Humans
Infant
Infant, Newborn
Liver Diseases
Male
Marine Toxins
Microcystins
Middle Aged
Models, Theoretical
United States
Young Adult

Chemicals

Bacterial Toxins
Cyanobacteria Toxins
Marine Toxins
Microcystins

Word Cloud

Created with Highcharts 10.0.0liverdiseasecyanobacterialbloomsnon-alcoholicUnitedStatesriskcoveragestudyspatialBayesianclustersdeathassociationbloom0levelhealthevidencetoxinsstatisticalanalysisecologicalgenderageMERISwatertoolusedsignificantregressioncoastalareasshowed1%countyBACKGROUND:HarmfulpresentglobalthreathumansuggestingcancausedamagecancerHoweverlittleepidemiologicresearcheffectshumansexcessremainsuncertainpurposeestimatedistributionconducttesthypothesiscontaminationpotentialfactorMETHODS:designemployedcounty-specificstandardizedmortalityratesSMRcomputed19992010BloommapsproducedbasedestimatedphycocyaninlevelsMediumResolutionImagingSpectrometercolorimageries08/01/200509/30/2005scanidentifymaplocalindicatorLISAmodelanalyzerelationshipRESULTS:Cyanobacterialfoundwidelyspreadincluding62%counties19493109signsmeasuredSignificantdeathsattributableidentifiedimpactedsignificantlyrelatedincreased3%95%CI5%increaseaffectedadjustingeducationalraceCONCLUSIONS:populationstatisticallycontiguousRemotesensing-basedmonitoringprovidesusefulassessinghazardsadditionalstudiesneededestablishspecificCyanobacteriadisease:

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