Maternal iodine status is important for the growth and development of fetus. Severe iodine deficiency or iodine excess is related to adverse fetus outcomes [
16]. The World Health Organization (WHO) currently recommends using UIC from spot urine samples to describe the iodine status of a population. Despite the WHO recommendation, the sampling is convenient. 24-h urinary iodine excretion (UIE) was used as a reference standard for estimation of iodine intake. In our follow-up of more than a year, urine volume was affected by climate and drinking water, and fluctuated greatly. Therefore, we consider the operability and convenience of collection, and used spot urine to evaluate iodine nutritional status. The WHO recommends that the median UIC for pregnant women is 150–249 μg/L [
17]. This study showed that the median UIC for pregnant women was 172 ± 135 μg/L (sufficient by WHO criteria) which was similar compared with previous study which included 2087 pregnant women in Wuhan City, another city in Hubei Province and found that the average UIC was 178 μg/L. Universal salt iodization is the first-line strategy for the elimination of severe iodine deficiency. After the implementation of a USI policy [
18], China has nearly wiped out IDD in the past two decades. In addition, increasing dietary iodine intake is an important manner to prevent iodine deficiency. Authorities recommend that pregnant women should supplement 150 mg iodine daily to achieve a total daily iodine intake of 250 mg [
19]. Here, we found significant associations between iodine contained supplements and UIC though only 14.3% of pregnant women in this cohort took iodine contained supplements. What’s more, it comes from multivitamin (containing iodine) supplements. A positive significant correlation between UIC and more frequent milk consumption was found which was consistent with previous studies [
20‐
23]. Seafood is still the main food source of iodine and positively correlated with UIC in vivo. A study conducted in Korea showed a significant correlation between dietary iodine in seaweed and UIC [
24]. However, in central China, seafood is not the main diet for residents, and only 15.5% of the subjects in this study consumed seafood frequently, so there was no significant correlation between seafood consumption and UIC. In this cohort, 90.7% of pregnant women used iodized salt, which was associated with higher UIC compared to pregnant women not taking iodized salt. According to the urinary iodine level of Chinese residents, the amount of iodine in iodized salt is always changing. In 2011, the Ministry of Health of the People’s Republic of China issued the “iodine content of edible salt”, which stipulates that the average level of iodine content in edible salt can be divided into 20 mg/kg, 25 mg/kg and 30 mg/kg. One or two kinds of iodized salt can be selected according to the iodine nutrition level of people in the province in China. Xiangyang and Pingdingshan municipal government both chose 25 mg/kg standard. We confirmed the amount of iodization through the salt package provided by pregnant women. But still not sure if this dose is appropriate for each individual. Clinical factors, such as multivitamin supplements containing iodine and dietary intake are considered risk factors for iodine excess. We recalculated odds ratio (OR) value in multivariable logistic regression model, and found that two variables, multivitamin supplements with iodine and frequent milk consumption, with OR greater than 1 and P less than 0.05, were regarded as risk factors for more than adequate iodine (UIC ≥ 250 μg/L) (Supplementary Table
2). However, they are not independent risk factor. However, the increase of thyroid diseases related to excessive iodized salt has become a new public health problem [
25‐
27]. The harm of iodine excess to pregnant women and fetus, the recommended safe dose of iodine intake is controversial and, especially for women with mild to moderate iodine deficiency. Routine monitoring is necessary to guarantee adequate iodine status. Therefore, the present study aimed to assess iodine status in central China and explore the effect of maternal UIC on neonatal outcomes. Because the best indicator to evaluate iodine status is still controversial.
Infants with maternal UIC below 150 μg/L had lower birthweight, shorter femur length and smaller head circumference than those with maternal UIC between 250 and 449 μg/L in our study. Otherwise, this study demonstrated that neonatal features were associated with dairy food and supplements. Iodine supplement, seafood, milk, yogurt intake and iodized salt consumption were positively associated with birthweight. This finding above was consistent with previous review which suggested the associations between iodized salt consumption and the increase of birthweight [
28,
29]. Significant difference was also found in birthweight among different UIC groups (the birthweight in the UIC ≥ 250 μg/L group was heavier). More macrosomia occurred in pregnant women with more than adequate iodine than in those with iodine deficiency (52.8% vs. 16.7%,
P = 0.001). Then multivariate logistic regression analysis was used to evaluate whether UIC was the risk factor for macrosomia risk. The result showed that more than adequate (UIC ≥ 250 μg/L) and iodine excess (UIC ≥ 500 μg/L) during pregnancy acted as risk factors for macrosomia. Therefore, for pregnant women in central China who generally ate iodized salt, they need to take iodine-containing multivitamin carefully. No correlation between UIC during the third trimester and first trimester of pregnancy and macrosomia was observed. High thyroid-stimulating hormone (TSH) (TSH > 4.94 nIU/l) or low free thyroxine (FT4) (FT4 < 9.01 pmol / L) had no adverse effect on macrosomia. Iodine deficiency was also not a risk factor for macrosomia (Supplementary Table
4). To monitor iodine status to prevent the risk of more than adequate iodine intake in pregnant women with normal UIC at present, thus avoiding the risk of adverse pregnancy outcomes such as macrosomia, the clinical model is established to monitor the iodine nutritional status of pregnant women in the central China to avoid more than adequate iodine intake, thus reducing the risk of having a macrosomia. Because the random urine iodine test can only represent the iodine level of this time and cannot fully reflect the iodine status in the body, nor can it show that iodized salt or iodine-rich diet intake is suitable, so how to predict the high-risk group of pregnant women with more than adequate iodine through multiple variables is meaningful, especial for pregnant women in central China who generally eat iodized salt, they need to take iodine-containing multivitamin or food carefully. In the machine learning framework, in brief, this is an online model. The model is based on the data of 870 pregnant women. The intake of iodized salt and the frequency of milk and other iodine-rich diet was taken as variables and input into the model, which have different important values (Supplementary Fig.
4). Then they will get a prediction score, which indicates the iodine nutritional status of the pregnant women, especially the pregnant women whose UIC showed that iodine was adequate can avoid iodine excess via adjustment measures given by the model. We believe that the combination of multiple risk factors is more effective in predicting risk than single indicator such as random spot urinary iodine or 24-h UIE. Then clinical guidance such as replacing iodine contained salt or supplements to non-iodine ones or reducing iodine-rich food can be output according to the risk range, and the frequency of reduction can be output, thus helping clinicians to provide prevention for more than adequate iodine intake in the pregnant women in different pregnant time. For pregnant women whose UIC has exceeded the adequate range, they can cooperate with the UIC value to evaluate the iodine-rich diet of pregnant women and give adjustment measures. The sample was relatively small in this study, thus a large population in the further studies will be analyzed to verify the role of the monitor models in clinical practice.