Objective:To explore the effect of physical development on thyroid volume of children aged 8 - 10 years in Sichuan Province, and explore the thyroid volume correction method suitable for school-age children, so as to accurately prevent and control iodine deficiency disorders.Methods:From June to July 2020, Shuangliu District of Chengdu City, Pengshan District of Meishan City, Miyi County of Panzhihua City and Qingchuan County of Guangyuan City were selected as the survey counties (districts). One township (town and street) was selected from each county (district) according to the five directions of East, West, South, North and Middle, one primary school was selected from each township (town and street), and 40 children aged 8 - 10 years (gender and age balanced) were selected as the survey subjects from each primary school, height and weight were measured, the body mass index (BMI) and body surface area (BSA) were calculated. Thyroid volume was measured by B-ultrasound, and the different thyroid volume indexes [height volume index 1 (HVI1), height volume index 2 (HVI2), body mass volume index (BMIV), weight and height volume index (WHVI), body surface volume index (BSAV)] were calculated, respectively. Urine samples of all children were collected, the iodine concentration in urine was measured, and the correlation between different measurement indexes and children's growth and development indexes was analyzed.Results:A total of 805 children aged 8 - 10 years were investigated, including 403 boys and 402 girls. There were 312, 288 and 205 children in the 8-, 9- and 10-year-old groups, respectively. A total of 805 urine samples were collected, and the median urinary iodine was 251.4 μg/L. There was no statistically significant difference in thyroid volume between boys and girls ( Z = - 0.44, P = 0.661), but was statistically significant difference between ages ( H = 64.95, P < 0.001). In all age groups, thyroid volume was positively correlated with height and weight (8-year-old group: r = 0.29, 0.42, P < 0.001; 9-year-old group: r = 0.29, 0.41, P < 0.001; 10-year-old group: r = 0.34, 0.47, P < 0.001). In all age groups, after HVI1 correction, thyroid volume was positively correlated with height and weight (8-year-old group: r = 0.13, 0.32, P < 0.05; 9-year-old group: r = 0.12, 0.30, P < 0.05; 10-year-old group: r = 0.18, 0.37, P < 0.05). In all age groups, there was a positive correlation between thyroid volume and weight after HVI2 correction (8-year-old group: r = 0.20, P < 0.001; 9-year-old group: r = 0.17, P = 0.004; 10-year-old group: r = 0.26, P < 0.001). In the 8- and 10-year-old groups, there was a positive correlation between thyroid volume and height after BMIV correction ( r = 0.20, P < 0.001; r = 0.21, P = 0.003). In all age groups, there was a negative correlation between thyroid volume and height and weight after WHVI correction (8-year-old group: r = - 0.35, - 0.37, P < 0.001; 9-year-old group: r = - 0.38, - 0.39, P < 0.001; 10-year-old group: r = - 0.31, - 0.38, P < 0.001). In the 8-year-old group, there was a positive correlation between thyroid volume and weight after BSAV correction ( r = 0.11, P = 0.045). Conclusions:Thyroid volume is closely related to height and weight. It may be inappropriate to judge goiter in children only based on age. After the preliminary comparison of five correction methods, it is found that BSAV is better.

Objective:To study the iodine nutrition status of key populations in Sichuan Province, so as to provide a basis for scientific supplementation of iodine and adjustment of prevention and control measures.Methods:From 2018 to 2022, the stratified cluster sampling method was used in 21 counties (district) in Sichuan Province. Each county (district) was divided into 5 areas based on east, west, south, north, and center. One township (street) was selected as a monitoring site from each area. Forty children aged 8 - 10 years old and 20 pregnant women, women of childbearing age, lactating women, and their infants and young children (0 - 2 years old) were randomly selected from each monitoring site. Household edible salt and urine samples were collected for salt and urine iodine testing. B-ultrasound method was used for thyroid examination in children.Results:A total of 52 019 samples of edible salt were collected, including 50 084 qualified iodized salt samples. The qualified iodized salt consumption rate was 96.3%, and the median salt iodine was 27.1 mg/kg. A total of 21 021 urine samples from children were tested, with a median urine iodine level of 199.5 μg/L. A total of 10 293 urine samples were taken from pregnant women, and the median urine iodine level was 172.6 μg/L. A total of 10 502 urine samples were taken from women of childbearing age, with a median urine iodine level of 174.4 μg/L. A total of 10 444 urine samples were taken from lactating women, and the median urine iodine level was 164.9 μg/L. There were 10 442 urine samples from infants and young children, and the median urine iodine level was 191.9 μg/L. A total of 21 028 children underwent thyroid examination, with a goiter rate of 1.8% (370/21 028).Conclusion:From 2018 to 2022, the iodine nutrition of key populations in Sichuan Province is at an appropriate level, and the elimination of iodine deficiency disorders continues to be maintained.

Objective:To investigate the effects of combined exposure of arsenic and high-fat diet (HFD) on serum adiponectin in mice.Methods:According to the 2 × 3 factorial design, a total of 90 male C57BL/6 mice were randomly divided into 6 groups using random number table method based on body weight (16-22 g): standard diet (STD) control group, STD+ 5 mg/L arsenic group, STD+ 50 mg/L arsenic group, HFD control group, HFD+ 5 mg/L arsenic group and HFD+ 50 mg/L arsenic group. There were 15 mice in each group, and sodium arsenite (NaAsO 2) was added to the drinking water. Mice were accessed freely to water and fed ad libitum. After 17 weeks, urine samples, fasting blood samples and adipose tissue were collected. Urinary arsenic was determined by atomic fluorescence. Blood glucose meter was used to measure blood glucose. Levels of blood lipid contents, including serum triglyceride (TG), total cholesterol (TC), and high density lipoprotein cholesterol (HDL)-c, were examined by kit enzymatic method. Levels of insulin, total adiponectin and high molecular weight (HMW) adiponectin were examined by enzyme-linked immunosorbent assay. Results:There was no interaction between arsenic exposure and HFD on the effects of blood glucose and blood lipids ( P > 0.05). There was an interaction between these two factors on serum insulin and total adiponectin ( P < 0.05). HFD can significantly increase blood glucose, serum TC levels ( P < 0.05), but not TG and HDL-c in mice ( P > 0.05). The levels of TG and HDL-c in STD+ 50 mg/L arsenic group were significantly decreased as compared to those of STD control group (mmol/L: 0.72 ± 0.14 vs 0.88 ± 0.24, 0.67 ± 0.03 vs 0.80 ± 0.16, P < 0.05). Compared with STD control group, there was no significant difference in serum insulin level in HFD control group and STD+ 5 or 50 mg/L arsenic groups ( P > 0.05), but insulin levels in HFD+ 5 or 50 mg/L arsenic groups were significantly decreased (mU/L: 14.71 ± 4.16 vs 11.42 ± 0.78, 11.52 ± 1.53, P < 0.05). Compared with STD control group, serum total adiponectin, HMW adiponectin levels, and the ratio of HMW adiponectin to total adiponectin were significantly reduced in HFD control group and STD+ 5 or 50 mg/L arsenic groups ( P < 0.05). In HFD+ 5 mg/L arsenic group, the above indexes of adiponectin were significantly higher than those of the HFD control group ( P < 0.05). In STD groups, an inverse relationship was observed between log transformed urinary total arsenic concentrations and serum levels of total adiponectin and HMW partial correlation coefficient ( r=- 0.549,-0.608, P < 0.01). Conclusions:Both arsenic exposure and HFD can alter glucose and lipid metabolism in mice, but their manifestations are different. Arsenic exposure and HFD can synergistically reduce serum insulin levels, and have an antagonism on serum adiponectin.

Inorganic arsenic is an environmental carcinogen.Chronic exposure to inorganic arsenic has also been suggested being associated with diabetes mellitus and cardiovascular disease, which is a prominent feature of glycolipid metabolism disorders. This article describes the current findings from epidemiological studies on arsenic exposure and diabetes and cardiovascular disease, as well as the possible mechanisms underlying the regulation of glycolipid metabolism after arsenic exposure. It is demonstrated that the effect of arsenic exposure on glycolipid metabolism is mediated through multiple mechanisms that are interrelated, rather than by a single mechanism, eventually leading to diabetes mellitus and cardiovascular disease.