A county-level spatial epidemiological study of hair selenium and Keshan disease

Background

No spatial analysis of hair selenium and Keshan disease (KD) on a nationwide county-level has been performed. Selenium deficiency is a recognized environmental risk factor for KD. Hair selenium is one of the recognized biomarkers of selenium nutrition. This study aimed to perform a geographically precise and visualized assessment of the achievement of KD prevention and control at the level of selenium nutrition in terms of etiology.

Methods

A spatial ecological study was conducted. The hair selenium content of the residents was assayed using an atomic fluorescence spectrometer. The spatial analysis was performed using ArcGIS.

Results

The median of the hair selenium levels of the 3,028 participants in the 1,174 counties was 0.38 mg/kg, and the content of inhabitants in KD endemic counties was significantly lower than that in KD non-endemic counties (0.34 vs. 0.39 mg/kg, z = −10.03, P < 0.0001). The proportion of Se-deficient and Se-marginal counties in KD endemic counties was significantly higher than that in KD non-endemic counties (59.4 vs. 29.0%, z = −7.45, P < 0.0001). The global autocorrelation analysis was not statistically significant (Moran's I = 0.0005, P = 0.68). Local autocorrelation analysis identified 174 low-low clusters of hair selenium levels, 83 (47.7%) of which are KD endemic counties located in KD endemic provinces of Henan, Gansu, Shaanxi, Inner Mongolia, Jilin, and Heilongjiang. The hair selenium featured a positive correlation with per capita GDP (rs = 0.20, P < 0.0001).

Conclusion

The median of the hair selenium levels of inhabitants living in KD endemic counties was significantly lower than that in KD non-endemic counties. All the 83 KD endemic counties with low-low clusters of hair selenium levels should be prioritized in KD precision prevention and control. These findings are geographically precise and visualized evidence of the assessment of the effectiveness of KD prevention and control at the level of selenium nutrition in terms of etiology.

Spatial Epidemiological Analysis of Keshan Disease in China

Objectives:

Few researchers have studied the national prevalence of Keshan disease (KD) in China using spatial epidemiological methods. This study aimed to provide geographically precise and visualized evidence for the strategies for KD prevention and control.

Methods:

We surveyed and analyzed 237,000 people in 280 out of 328 KD-endemic counties (85.4%) in mainland China using a design of key investigation based on case-searching in 2015–2016. ArcGIS version 9.0 was used for spatial autocorrelation analysis, spatial interpolation analysis and spatial regression analysis.

Results:

Global autocorrelation analysis showed that global clustering of latent Keshan disease (LKD) prevalence was noted (Moran’s I = 0.22, Z = 7.06, and P < 0.0001), no global clustering of chronic Keshan disease (CKD) prevalence (Moran’s I = 0.03, Z = 1.10, and P = 0.27) was observed. Spatial regression analysis showed that LKD prevalence was negatively correlated with per capita disposable income (t = –4.36, P < 0.0001). Local autocorrelation analysis at the county level effectively identified the cluster areas of LKD prevalence in the provinces of Shaanxi, Gansu, Shanxi, Inner Mongolia, and Jilin. The high-high cluster areas should be given priority for precision prevention and control of Keshan disease.

Conclusions:

This spatial epidemiological study revealed that LKD prevention and control should be strengthened in areas with high values of clustering. Our findings provided spatially, geographically precise and visualized evidence for prioritizing KD prevention and control.

A County-Level Spatial Study of Serum Selenoprotein P and Keshan Disease

Background

Keshan disease (KD) is strongly associated with selenium deficiency. Selenoprotein P (SELENOP) is a recognized molecular biomarker of selenoproteins and an important indicator of selenium nutrition. This study was aimed at providing geographically precisely visualized evidence of selenium nutrition at molecular level for assessing KD prevention, control, and elimination on the etiological perspective.

Methods

We used spatial ecological design for this study. The serum SELENOP levels of the residents were measured by ELISA. ArcGIS version 9.0 was used for spatial description, spatial autocorrelation analysis of SELENOP levels and spatial regression with per capita disposable income.

Results

The mean serum SELENOP levels of the 6,382 residents in 1,688 counties were 4.62 ± 1.82 μg/mL. The mean serum SELENOP levels of the residents living in the townships and rural areas of KD endemic counties were not statistically significantly lower than those of the KD non-endemic counties. The mean serum SELENOP levels were globally clustered (Moran's I = 0.03, z = 6.37, and P < 0.0001), and 99.3% (553/557) of the cold spots, identified by local autocorrelation analysis (Getis-Ord-Gi^* analysis), were located in the KD endemic provinces of Shaanxi, Shanxi, Henan, Hebei, Shandong, Inner Mongolia, Gansu, Hubei, Chongqing, Yunnan, and Sichuan. The serum SELENOP level was positively correlated with per capita disposable income (t = 3.52, P = 0.0004).

Conclusions

The results of this study were the geographically precisely visualized evidence of selenium nutrition at molecular level for assessing KD elimination on the etiological perspective. The cold spot counties found by Getis-Ord-Gi^* analysis in the KD endemic provinces should be the high priority of KD precision prevention and control.

A spatial study on serum selenoprotein P and Keshan disease in Heilongjiang Province, China

BACKGROUND

Few spatial studies on serum selenoprotein P (SELENOP) and Keshan disease (KD) have been reported at the county-level in Heilongjiang province, China. This study aimed to provide visualized spatial epidemiological evidence of selenium molecular marker in residents living in endemic areas for the precise assessment of prevention, control, and elimination of KD.

METHODS

Using a spatial ecological study design, 587 subjects living in cities, townships, and rural areas of 50 KD endemic counties and 37 non-endemic counties in Heilongjiang province were investigated. The serum SELENOP levels of the participants were measured by enzyme-linked immunosorbent assay. Thematic maps were created, and spatial regression analysis was conducted using ordinary least squares.

RESULTS

The mean serum SELENOP level of the 587 subjects was 7.4 ± 3.0 μg/mL. The mean levels of serum SELENOP were higher in cities (7.4 ± 2.9 μg/mL) and townships (7.9 ± 3.2 μg/mL) than in rural areas (6.0 ± 3.0 μg/mL). The mean levels of serum SELENOP were trending towards high levels in non-endemic areas (7.4 ± 3.0 μg/mL) than in KD endemic areas (6.3 ± 3.3 μg/mL). Spatial regression analysis showed that the serum SELENOP level was positively correlated with the per capita gross domestic product.

CONCLUSION

Selenium deficiency may still exist in some KD endemic counties in Heilongjiang province, including Lingdong, Nenjiang, and Baiquan; these counties should be considered as key areas for precision prevention, control, and elimination of KD. Inclusion of selenium in the national surveillance of KD will provide more evidence for the assessment of KD elimination from a selenium nutrition perspective.