Background: The current national growth and development standard of preschool children in China was formulated in 2003, which has many deficiencies. It is necessary to construct more scientific percentile curve and growth reference standards in order to evaluate more effectively the growth, development and health status of Chinese children.
Methods: Based on the physical and health data of 31 provinces in China measured in 2010 and 2014, the GAMLSS model was used to construct the growth reference standard and correlation curve.
Results: We obtained growth reference standards for percentile curve and Z-score curve of height-for-age, sitting height-for-age, Weight-for-age, Chest circumference-for-age of Chinese preschool children. The C50 percentile of all indicators showed an obvious increasing trend with aged 3.0 to 6.5. Such as, the height of boys and girls increased by 21.1cm and 20.3cm respectively, the sitting height boys and girls increased by 10.3cm and 10.1cm respectively, the weight of boys and girls increased by 7.1 kg and 6.3 kg respectively, the Chest circumference of boys and girls increased by 6cm and 5.2 cm respectively.
Conclusion: The children's growth and development charts provided in this study provide effective monitoring and personalized evaluation tools for the growth and development assessment of preschool children, as well as for the reduction of malnutrition, prevention and control of childhood obesity. It is recommended to be used in some areas such as child health, medical treatment and public health.
In order to explore the application of artificial neural network in rehabilitation evaluation, a kind of ANN stable and reliable artificial intelligence algorithm is proposed. By learning the existing clinical gait data, this method extracted the gait characteristic parameters of patients with different ages, disease types and course of disease, and repeated data iteration and finally simulated the corresponding gait parameters of patients. Experiments showed that the trained ANN had the same score as the human for most of the data (82.2%, Cohen’s kappa = 0.743). There was a strong correlation between ANN and improved Ashworth scores as assessed by human raters (r = 0.825,
P
<
0.01
). As a stable and reliable artificial intelligence algorithm, ANN can provide new ideas and methods for clinical rehabilitation evaluation.
Background: We aimed to establish a reference standard of Body Mass Index (BMI) for the growth of preschool children in China. Methods: We monitored and obtained the height and weight of 50702 children aged 3-6 yr in 31 provinces in mainland China in 2014. The reference standard and percentile curve of BMI preschool children aged 3-6 yr old were formulated by using Lambda-Median-Sigma (LMS) method in China. Results: The common grounds of the male and female children were as follows: the percentile maps were similar in shape; the graphs of children aged 4-6 were approximately horn shaped. The differences between male and female children were as follows: the BMI values of male children in the same age group and the same percentile were higher than those of the female children. The change pattern of male children was larger than that of female children. BMI of 3 yr old and 6 yr old children was larger than those of 4 yr old and 5 yr old. During the change from low percentile to high percentile, the BMI values of Chinese male children exceeded WHO to a larger extent, and the BMI values of Chinese female children were substantially consistent with WHO, but the high percentile greater than P95 exceeded WHO. Conclusion: The BMI growth chart developed can be applied in monitoring the growth and nutrition of preschool children in China. We recommend the promotion of the results in the field of preventive health care.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.