Spatial distribution of iodine content in residential drinking water in Shaanxi Province in 2022
10.3760/cma.j.cn231583-20250226-00074
- VernacularTitle:2022年陕西省居民生活饮用水碘含量空间分布情况分析
- Author:
Shanshan LI
1
;
Yunpeng NIAN
;
Xuejuan GAO
;
Gang NIU
;
Dawei GUO
;
Lieqing HUANG
;
Gang DUAN
Author Information
1. 陕西省疾病预防控制中心地方病预防控制所，西安 710003
- Publication Type:Journal Article
- Keywords:
Iodine;
Spatial distribution;
Clustering
- From:
Chinese Journal of Endemiology
2025;44(11):890-894
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To study the spatial distribution and characteristics of iodine content in residential drinking water in Shaanxi Province, and provide a basis for scientific prevention and control of iodine deficiency disorders.Methods:From March to October 2022, an investigation was conducted in all counties (districts, referred to as counties) of Shaanxi Province, with administrative villages as survey units. For centralized water supply systems, two terminal water samples were collected, and iodine content was measured separately, with the average value representing the drinking water iodine content at that location. For decentralized water supply systems, a 10% sampling method was used to divide each administrative village into five areas (east, south, west, north, and center), with 10% of water wells sampled from each area (if fewer than 10 water wells, the well with the largest drinking population was selected; if fewer than 5 wells, all wells were sampled). One water sample was collected from each water well, and iodine content was determined using the arsenic-cerium catalytic spectrophotometry method. Spatial autocorrelation and spatial scan analysis were used to analyze the spatial distribution and characteristics of drinking water iodine content.Results:A total of 53 990 drinking water samples were collected, with a median water iodine content of 6.66 μg/L, ranging from 0.10 to 779.40 μg/L. Drinking water iodine content was detected in 112 counties, showing a significant spatial positive correlation (global autocorrelation, Moran's I = 0.74, Z = 43.83, P < 0.001). Local autocorrelation analysis showed that the difference in the distribution of iodine content in drinking water among 36 counties was statistically significant ( P < 0.05), with 22 counties showing low-low clustering and 12 counties showing high-high clustering. Spatial scanning identified three water iodine clustering areas, including two high-water iodine cluster areas and one low-water iodine cluster area. Conclusions:The distribution of iodine content in residential drinking water in Shaanxi Province shows significant spatial clustering and heterogeneity, requiring targeted interventions to achieve precise prevention and control of iodine deficiency disorders.
