BACKGROUNDInformation on LMS parameters and percentiles reference for Saudi children and adolescents is not available.OBJECTIVETo report the L, M, and S parameters and percentile reference graphs for growth.DESIGNField survey of a population-based sample of Saudi school-age children and adolescents (5–18 years of age).SETTINGA stratified listing of the Saudi population.SUBJECTS AND METHODSData from the national study of healthy children were reanalyzed using the Lamba-Mu-Sigma (LMS) methodology. The LMS parameters of percentiles for weight, height, and body mass index for age were calculated for children and adolescents from 5 to 18 years of age.MAIN OUTCOME MEASUREThe main outcomes were the LMS parameters and percentiles of growth.RESULTSThere were 19 299 and 9827 (50.9%) were boys. The data for weight, height, and BMI for age for boys and girls are reported for the 3rd, 5th, 10th, 25th, 50th, 75th, 90th, 95th, and 97th percentiles including LMS parameters for each percentile and age. Figures corresponding to each table are color coded (blue for boys and pink for girls).CONCLUSIONSThis report provides a reference for growth and nutrition of Saudi school-age children and adolescents. The detailed LMS and percentile tables and graphs provide essential information for clinical assessment of nutritional status and growth in various clinical conditions and for research.LIMITATIONSThis report does not reflect regional variations in growth.
Digitalization of healthcare delivery is rapidly fostering development of precision medicine. Multiple digital technologies, known as telehealth or eHealth tools, are guiding individualized diagnosis and treatment for patients, and can contribute significantly to the objectives of precision medicine. From a basis of “one-size-fits-all” healthcare, precision medicine provides a paradigm shift to deliver a more nuanced and personalized approach. Genomic medicine utilizing new technologies can provide precision analysis of causative mutations, with personalized understanding of mechanisms and effective therapy. Education is fundamental to the telehealth process, with artificial intelligence (AI) enhancing learning for healthcare professionals and empowering patients to contribute to their care. The Gulf Cooperation Council (GCC) region is rapidly implementing telehealth strategies at all levels and a workshop was convened to discuss aspirations of precision medicine in the context of pediatric endocrinology, including diabetes and growth disorders, with this paper based on those discussions. GCC regional investment in AI, bioinformatics and genomic medicine, is rapidly providing healthcare benefits. However, embracing precision medicine is presenting some major new design, installation and skills challenges. Genomic medicine is enabling precision and personalization of diagnosis and therapy of endocrine conditions. Digital education and communication tools in the field of endocrinology include chatbots, interactive robots and augmented reality. Obesity and diabetes are a major challenge in the GCC region and eHealth tools are increasingly being used for management of care. With regard to growth failure, digital technologies for growth hormone (GH) administration are being shown to enhance adherence and response outcomes. While technical innovations become more affordable with increasing adoption, we should be aware of sustainability, design and implementation costs, training of HCPs and prediction of overall healthcare benefits, which are essential for precision medicine to develop and for its objectives to be achieved.
BACKGROUND AND OBJECTIVES:No previous study has provided a detailed description of regional variations of growth within the various regions of Saudi Arabia. Thus, we sought to demonstrate differences in growth of children and adolescents in different regions.SUBJECTS AND METHODS:The 2005 Saudi reference was based on a cross-sectional representative sample of the Saudi population of healthy children and adolescents from birth to 18 years of age. Body measurements of the length, stature, weight, head circumference and calculation of the BMI were performed according to standard recommendations. Percentile construction and smoothing were performed using the LMS (lambda, mu and sigma) methodology, followed by transformation of all individual measurements into standard deviation scores. Factors such as weight for age, height for age, weight for height, and head circumference for children from birth to 3 years, stature for age, head circumference and body mass index for children between 2-18 years of age were assessed. Subsequently, variations in growth between the three main regions in the north, southwest, and center of Saudi Arabia were calculated, with the Bonferroni: method used to assess the significance of differences between regions.RESULTS:There were significant differences in growth between regions that varied according to age, gender, growth parameter and region. The highest variation was found between children and adolescents of the southwestern region and those of the other two regions The regression lines for all growth parameters in children <3 years of age were significantly different from one region to another reaching – 0.65 standard deviation scores for the southwestern regions (P=.001). However, the difference between the northern and central regions were not significant for the head circumference and for weight for length. For older children and adolescents a significant difference was found in all parameters except between the northern and central regions in BMI in girls and head circumference in boys. Finally, the difference in head circumference of girls between southwestern and northern regions was not significant. Such variation affected all growth parameters for both boys and girls.CONCLUSION:Regional variations in growth need to be taken into consideration when assessing the growth of Saudi children and adolescents.
BACKGROUNDAssessment of growth using Z-score methods is important for clinical care and research, yet growth reference Z-score data for preschool Saudi children are not available.OBJECTIVEEstablish Z-score tables and corresponding growth charts.DESIGNUses data from a national survey in 2004–2005.SETTINGCommunity-based random sample of preschool Saudi children.SUBJECTS AND METHODSRaw data from the previous nationally representative sample were analyzed using the L, M, and S statistical methods to calculate Z-scores of growth.MAIN OUTCOME MEASURE(S)Z-scores reference values for weight, length/height, head circumference, weight for length/height, and body mass index for age for boys and girls from birth to 60 months of age.RESULTSFor 15 601 Saudi children (7896, 50.6 % boys) Z-score tables and graphs from birth to 60 months of age were derived for boys and girls. The tables and graphs include weight for age, length/height for age, head circumference for age, weight for length/height, and BMI for age.CONCLUSIONZ-score reference data on the growth of preschool Saudi infants and children is essential for healthcare and research.LIMITATIONDoes not include regional variations.
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