Exploring the Link between Physiological Development and Intellectual Proficiency among Middle School Students in Linxia Hui Autonomous Prefecture, Gansu Province, China

Exploring the Link between Physiological Development and Intellectual Proficiency among Middle School Students in Linxia Hui Autonomous Prefecture, Gansu Province, China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Exploring the Link between Physiological Development and Intellectual Proficiency among Middle School Students in Linxia Hui Autonomous Prefecture, Gansu Province, China Yanling Wang, Qinglin Li, Jing Zhen, Wei Sun, Aiwei He, Xiaonan Zhu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4002108/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract OBJECTIVES: Is there a correlation between the growth trajectory of middle school students and their intelligence proficiency. METHODS: A cross-sectional survey was conducted in 2019, involving a total cohort of 1682 students.This survey assess their growth and development status by measuring height and weight and calculating body mass index (BMI). The intelligence of the sampled students was evaluated using the second revision of the Chinese Combined Raven Test (CRT-C2). Ordered logistic regression analysis was employed to comprehensively explore the relationship between their growth and developmental status and IQ. RESULTS: This height disparity between male and female was statistically significant ( χ 2 = 28.746, p = 0.000). Gender-based differences were observed in IQ scores, with girls outscoring boys ( χ 2 = 26.1, p = 0.000). Younger students exhibited higher IQ scores ( χ 2 =498.959, p = 0.000). Further analysis demonstrated that growth retardation ( OR = 2.675, 95% CI 1.189~6.018, p = 0.017), wasting( OR = 1.683, 95% CI 1.016~2.561, p = 0.015), overnutrition ( OR = 1.748, 95% CI 1.214~2.516, p = 0.003), low height development ( OR =1.816, 95% CI 1.313~2.511, p = 0.000) and middle height development ( OR = 1.433, 95% CI 1.095~1.875, p = 0.009) were identified as risk factors for middle school students in this region. CONCLUSION: The research highlights significant that growth retardation, wasting, overnutrition , low and middle height development were detrimental to intellectual development among middle school students in the region. Health sciences/Risk factors Health sciences/Health care/Nutrition INTRODUCTION The secondary school period is a critical phase of pubertal growth and development, ranking second in significance only to infancy but extending over a more protracted duration. Consequently, the nutritional requisites during this pivotal epoch are anticipated to surpass those encountered in any other developmental stage. Hence, the paramount importance of securing adequate nutrition remains pivotal in the endeavor to realize the full spectrum of growth potential[ 1 ]. In many developing countries, adolescent stunting, underweight, and micronutrient deficiencies were often result from a combination of malnutrition in early childhood and an inadequate diet to meet the intense nutritional requirements for rapid adolescent growth[ 2 ]. According to a 2020 World Health Organization report, approximately 47 million children under 5 years old worldwide suffered from wasting, while around 144 million were affected by stunting[ 3 ]. Furthermore, an estimated 200 million school-aged children globally grappled with malnourishment, with malnutrition implicated in approximately 45% of child mortality cases[ 4 ]. Children's capacities evolve through intricate interactions between their developing brains and environmental factors during the formative years[ 5 ], Previous investigations conducted in Northwest China have underscored the challenges posed by disadvantaged geographical environments and lower economic status in this region[ 6 ]. As a multi-ethnic enclave in Northwest China and a focal point of national poverty alleviation efforts, Linxia Hui Autonomous Prefecture boasts distinct residential settings, cultural backgrounds, and dietary patterns compared to other regions. To comprehensively understand the growth and cognitive aptitude of middle school students aged 11 to 18 in this unique context, this study conducted an assessment in 2019, through a survey of the nutritional status and intelligence proficiency of local secondary school students. The aim was to provide a foundational basis for enhancing the growth and intellectual development of local middle school students. METHODS Survey object and sampling method In 2019, a comprehensive survey was undertaken, involving a total cohort of 1682 students. These students were selected from 8 counties (cities) within the administrative purview of Linxia Hui Autonomous Prefecture, Gansu Province, China. The geographical regions encompassed Linxia City, Linxia County, Yongjing County, Dongxiang County, Guanghe County, Kangle County, Hezheng County, and Jishishan County.The selection process adhered to the principles of convenience sampling, encompassing 2 to 5 townships in each county (city) and 1 to 2 secondary schools in each township.It is noteworthy that this study received ethical clearance from the Ethics Committee of the Gansu Provincial Center for Disease Control and Prevention (Approval No. [031], 2021). Furthermore, it is pertinent to mention that all participating students provided informed consent through the signing of consent forms, thereby ensuring their voluntary and informed participation in the study. Survey content and method Measurement of physical indicators The gender and age of all subjects were meticulously recorded, and their height was assessed following a standardized procedure, with precision to the nearest 0.1 cm. Weight measurements were conducted using a consistent type of weight scale, with subjects removing their shoes to ensure accuracy, and measurements were recorded with precision to the nearest 0.1 kg. Evaluation of nutritional status Body mass index (BMI) serves as an objective indicator of growth and development and represents a commonly employed metric for assessing nutritional status. BMI calculations were derived from height and weight data, utilizing the formula: BMI = weight (kg)/height 2 (m 2 ). The assessment of growth retardation and wasting, which includes both moderate and mild forms of wasting, was conducted in accordance with the guidelines outlined in the ‘Screening for Malnutrition in School-Age Children and Adolescents’ (WS/T456-2014)[ 7 ]. Furthermore, the determination of overweight and obesity status was executed following the protocols stipulated in the ‘Screening for Overweight and Obesity in School-Age Children and Adolescents’ (WS/T586-2018)[ 8 ]. Height development grade evaluation The assessment of height development grades followed the guidelines outlined in the ‘Standard for height level classification among children and adolescents aged 7 ~ 18 years’ (WS/T612-2018)[ 9 ]. the height development levels were categorized into five distinct tiers, as follows: height < − 2SD (standard deviations) was classified as inferior; -height ≥ − 2SD and + 1SD and ≤ + 2SD was considered middle-upper; Height > + 2SD was superior (Note: SD was standard deviation). It is important to note that the classification criteria were consistent across all age groups. IQ test The assessment of intelligence among the sampled students was conducted using the second Revised version of the Combined Raven’s Test (CRT-C2) designed for children in China. The administration of this test was overseen by provincial personnel who had undergone national training and possessed qualifications, holding the Raven Psychological Test Certificate. Intelligence scores were categorized into seven grades[ 10 ], as follows: very excellent (IQ ≥ 130), excellent (120 ~ 129), upper middle (110 ~ 119), middle (90 ~ 109), lower middle (80 ~ 89), marginal (70 ~ 79), and low (≤ 69). This comprehensive classification system allowed for a nuanced evaluation of the students' cognitive abilities. Quality control The investigation efforts were executed by a team of provincially trained professional and technical personnel. The consistency of investigators was maintained throughout the entire process, with strict adherence to the pertinent technical guidelines. Each stage of the investigation, spanning from training and sample selection to fieldwork, data collection, analysis, and compilation, was meticulously overseen by dedicated personnel with clearly defined responsibilities. In the realm of physical measurements, height and weight were ascertained using standardized measuring instruments to ensure uniformity and precision. Similarly, for intelligence assessments, testers adhered to predefined standards and conducted the tests conscientiously. To enhance data integrity, a consistent numbering system for survey data was implemented, complemented by real-time verification and dual data entry procedures. Statistical analysis Statistical analysis for this study was conducted using SPSS version 20.0 Descriptive statistics for count data were presented in terms of case numbers and percentages [n(%)], Chi-square test was employed. Additionally, to gauge the strength of the association between nutritional status and IQ, ordered logistic regression was utilized. RESULTS Demographic Profile of Middle School Students in Linxia Hui Autonomous Prefecture In this study, a comprehensive survey was conducted involving a total of 1682 middle school students. Of this cohort, 835 students (49.6%) were male, while 847 students (50.4%) were female. The age distribution ranged from 11 to 18 years, with an average age of (14.07 ± 0.961) years for the entire sample. Nutrition Status Assessment of Middle School Students in Linxia Hui Autonomous Prefecture As presented in Table 1 , the detection rate of growth retardation displaying statistically significant differences across age groups( χ 2 = 58.631, p < 0.001). Notably, there were no reported cases of malnutrition (moderate wasting and mild wasting) among 11-year-old middle school students. Furthermore, significant disparities were noted in the overall nutritional status of middle school students when considering gender ( χ 2 = 77.977, p < 0.001) and age ( χ 2 = 46.369, p < 0.001), as detailed in Table 2 . Table 1 Growth retardation of participants [n (%)] Variable n Growth retardation χ 2 p Yes No Sex Girls 835 11(1.3) 824 (98.7) 0.830 0.487 Boys 847 10 (1.2) 837 (98.8) Age 11 10 0 10 (100) 58.631 < 0.001 12 85 0 85 (100) 13 525 1 (0.2) 524 (99.8) 14 716 3 (0.4) 713 (96.2) 15 263 10 (3.8) 253 (91.6) ≥ 16 83 7 (8.4)) 76 (98.8) Total 1682 21 (1.2) 1661 (98.8) Table 2 Nutritional status of participants [n (%)] Variable n BMI ( \(\overline{\text{x}}\pm \text{s}\)) Wasting Normal Overnutrition χ 2 p Moderate wasting Mild wasting Subtotal Overweight Obesity Subtotal Sex Girls 835 18.3 ± 2.8 58 (6.9) 132 (15.8) 190 (22.7) 587 (70.3) 38 (4.6) 20 (2.4) 58 (7.0) 77.977 < 0.001 Boys 847 19.0 ± 2.7 34 (4.0) 35 (4.1) 69 (8.1) 727 (85.5) 32 (3.8) 19 (2.2) 51 (2.5) Age 11 10 20.2 ± 4.1 0 0 0 8 (80) 0 2 (20.0) 2 (20.0) 46.369 < 0.001 12 85 17.8 ± 1.9 1 (1.2) 5 (5.9) 6 (7.1) 76 (89.4) 3 (3.5) 0 3 (3.5) 13 525 18.4 ± 2.8 21 (4.0) 43 (8.2) 64 (12.2) 432 (82.3) 18 (3.4) 11 (2.1) 29 (5.5) 14 716 18.8 ± 2.8 36 (5.0) 83 (11.6) 119 (16.6) 540 (75.4) 37 (5.2) 20 (2.8) 57 (8.0) 15 263 18.8 ± 2.5 26 (9.9) 25 (9.5) 51 (19.4) 199 (75.7) 8 (3.0) 5 (1.9) 13 (4.9) ≥16 83 19.1 ± 2.6 8 (9.6) 11 (13.3) 19 (22.9) 59 (71.1) 4 (4.8) 1 (1.2) 5 (6.0) Total 1682 18.6 ± 2.7 92 (5.5) 167 (9.9) 259 (15.4) 1314 (78.1) 70 (4.2) 39 (2.3) 109 (6.5) Height Development Assessment among Middle School Students in Linxia Hui Autonomous Prefecture As delineated in Table 3 , the mean height of middle school students in Linxia Prefecture averaged at 159.3 ± 0.79 cm. This disparity in height development between male and female middle school students was statistically significant ( χ 2 = 28.746, p < 0.001). Furthermore, the middle school students in the region have statistically significant differences in height development across different age group ( χ 2 = 144.209, p < 0.001). Notably, among 11-year-old students, there were no reported cases of height development classified as inferior or lower middle. Similarly, among high school students aged ≥ 16, no instances of height development classified as superior levels were identified. Table 3 Height development of participants [n (%)] Variable n Height ( \(\overline{\text{x}}\pm \text{s}\)) Height Development χ 2 p Inferior Lower middle Middle Upper middle Superior Sex Girls 835 162.0 ± 0.08 62 (7.4) 148 (17.7) 530 (63.5) 81 (9.7) 14 (1.7) 28.746 < 0.001 Boys 847 156.7 ± 0.06 23 (2.7) 118 (13.9) 580 (68.5) 101 (11.9) 25 (19.6) Age 11 10 155.7 ± 0.09 0 0 5 (50.0) 3 (30.0) 2 (20.0) 144.209 < 0.001 12 85 156.3 ± 0.08 1 (1.2) 5 (5.9) 53 (62.4) 19 (22.4) 7 (8.2) 13 525 157.7 ± 0.07 8 (1.5) 65 (12.4) 386 (73.5) 53 (10.1) 13 (12.2) 14 716 160.3 ± 0.08 34 (4.7) 115 (16.1) 481 (67.2) 74 (10.3) 12 (1.7) 15 263 160.8 ± 0.08 29 (11.0) 53 (20.2) 150 (57.0) 26 (9.9) 5 (1.9) ≥ 16 83 160.2 ± 0.08 13 (15.7) 28 (33.7) 35 (42.2) 7 (8.4) 0 Total 1682 159.3 ± 0.79 85 (5.1) 266 (15.8) 1110 (66.0) 182 (10.8) 39 (2.3) Table 4 IQ of participants [n (%)] Variable n \(\overline{\text{x}}\pm \text{s}\) IQ χ 2 p Low(≤ 69) Marginal (70～79) Lower middle (80～89) Middle (90～109) Upper middle (110～119) Excellent (120～129) Very excellent (≥ 130) Sex Girls 835 99.85 ± 16.98 21 (2.5) 75 (9.0) 100 (12.0) 436 (52.2) 97 (11.6) 74 (8.9) 32 (3.8) 26.1 < 0.001 Boys 847 101.61 ± 17.03 28 (3.3) 66 (7.8) 96 (11.3) 374 (44.2) 169 (20.0) 80 (9.4) 34 (4.0) Age 11 10 114.40 ± 8.55 0 0 0 3 (30.0) 3 (30.0) 4 (40.0) 0 498.959 < 0.001 12 85 108.79 ± 12.61 0 1 (1.2) 4 (4.7) 41 (48.2) 24 (28.2) 10 (11.8) 5 (5.9) 13 525 107.36 ± 14.00 3 (0.6) 9 (1.7) 35 (6.7) 255 (48.6) 111 (21.1) 76 (14.5) 36 (6.9) 14 716 102.33 ± 14.98 8 (1.1) 38 (5.3) 89 (12.4) 377 (52.7) 118 (16.5) 62 (8.7) 24 (3.4) 15 263 86.47 ± 16.10 22 (8.4) 73 (27.8) 45 (17.1) 111 (42.2) 10 (3.8) 2 (0.8) 0 ≥ 16 83 80.35 ± 16.29 16 (19.3) 20 (24.1) 23 (27.7) 23 (27.75) 0 0 1 (1.2) Total 1682 100.73 ± 17.02 49 (2.9) 141 (8.4) 196 (11.7) 810 (48.2) 266 (15.8) 154 (9.2) 66 (3.9) Cognitive Intelligence (IQ) Status Among Middle School Students in Linxia Hui Autonomous Prefecture The mean IQ score for middle school students in Linxia Hui Autonomous Prefecture averaged at (100.7 ± 17.02). Significant disparities were observed in IQ values concerning gender distribution, with female students exhibiting higher IQ scores than their male counterparts( χ 2 = 26.1, p < 0.001). Additionally, IQ scores demonstrated variance across different age groups, with younger students achieving higher IQ score ( χ 2 = 498.959, p < 0.001), as shown in Table 4 . Comprehensive Assessment of Nutritional status, height development level, and IQ of middle school students in Linxia Hui Autonomous Prefecture As illustrated in Table 5 , there were no instances of middle school students with growth retardation who achieved IQ scores at or above the middle level. Similarly, there were no overweight or obese middle school students with low IQ scores. Furthermore, no middle school students with excellent height development exhibited low IQ scores, and there were no middle school students with inferior height development who attained excellent IQ scores. Table 5 Nutritional status, height development, and IQ of participants Variable n IQ χ 2 p Low (≤ 69) Marginal (70～79) Lower middle (80～89) Middle (90～109) Upper middle (110～119) Excellent (120～129) Very excellent (≥ 130) Growth retardation Yes 21 4 (19) 6 (28.6) 2 (9.5) 9 (42.9) 0 0 0 35.693 < 0.001 No 1661 45 (2.7) 135 (8.1) 194 (11.7) 801 (48.2) 266 (16.0) 154 (9.3) 66 (4.0) Nutritional status Mild wasting 92 5 (5.4) 16 (17.4) 9 (9.8) 43 (46.7) 7 (7.6) 8 (8.7) 4 (4.3) 78.729 < 0.001 Mild wasting 167 6 (3.6) 9 (5.4) 22 (13.2) 92 (55.1) 24 (14.4) 12 (7.2) 2 (1.2) Normal 1314 38 (2.9) 109 (8.3) 150 (11.4) 622 (47.8) 219 (16.7) 119 (9.1) 51 (3.9) Overweight 70 0 4 (5.7) 13 (18.6) 28 (40.0) 9 (12.9) 11 (15.7) 5 (7.1) Obesity 39 0 3 (7.7) 2 (5.1) 18 (48.7) 7 (17.9) 4 (10.3) 4 (10.3) Height Development Inferior 85 7 (8.2) 10 (11.8) 18 (21.2) 42 (49.4) 6 (7.1) 2 (2.4) 0 101.165 < 0.001 Lower middle 266 10 (3.8) 38 (14.3) 31 (11.7) 136 (51.1) 29 (10.9) 16 (6.0) 6 (2.3) Middle 1110 25 (2.3) 80 (7.2) 129 (11.6) 542 (48.8) 188 (16.9) 106 (9.5) 40 (3.6) Upper middle 182 7 (3.8) 12 (6.6) 17 (9.3) 16 (40.7) 15 (15.4) 5 (13.7) 19 (10.4) Superior 39 0 1 (2.6) 1 (2.6) 16 (41.0) 15 (38.5) 5 (12.8) 1 (2.6) Total 1682 49 (2.9) 141 (8.4) 196 (11.7) 810 (48.2) 266 (15.8) 154 (9.2) 66 (3.9) Ordered Logistic Regression Analysis of the Association Between Nutritional Status and IQ among Middle School Students in Linxia Hui Autonomous Prefecture The nutritional status was categorized into three distinct grades: wasting, overnutrition and normal, while height development was classified into lower, middle and upper grades. Meanwhile, the cognitive intelligence (IQ) levels were dependent variable across seven grades. Ordered logistic regression analysis was employed, utilizing growth retardation, nutritional status, and height development grade as independent variables. The results, as depicted in Table 6 , revealed that growth retardation ( OR = 2.675, 95% CI 1.189 ~ 6.018, p < 0.05), wasting( OR = 1.683, 95% CI 1.016 ~ 2.561, p < 0.05), overnutrition ( OR = 1.748, 95% CI 1.214 ~ 2.516, p < 0.05), low height development ( OR = 1.816, 95% CI 1.313 ~ 2.511, p < 0.01) and middle height development ( OR = 1.433, 95% CI 1.095 ~ 1.875, p < 0.05) were identified as risk factors for middle school students in this region. Specifically, middle school students without growth retardation in their nutritional status exhibited IQ scores 2.675 times higher than those of their counterparts with growth retardation. Moreover, students with normal nutritional status demonstrated IQ scores 1.683 times higher than those with wasting and 1.748 times higher than those with overnutrition. Additionally, students with high height development displayed IQ scores 1.816 times and 1.433 times higher than those with low and moderate height development, respectively . Table 6 Ordered logistic regression analysis of the relationship between nutritional status, height grade, and IQ Variable β SE Wald p OR 95% CI Growth retardation Yes 0.984 0.414 5.657 0.017 * 2.675 1.189 6.018 No - - - - - - - Nutritional status Wasting 0.521 0.356 4.014 0.015 * 1.683 1.016 2.561 Overnutrition 0.633 0.332 3.642 0.003 * 1.748 1.214 2.516 Normal - - - - - - - Height development Lower 0.597 0.165 13.029 0.000 ** 1.816 1.313 2.511 Middle 0.360 0.137 6.879 0.009 * 1.433 1.095 1.875 Upper - - - - - - - Note: * p <0.05; ** p <0.01 DISCUSSION Despite the continuous economic development, the nutritional status of children and adolescents in China has notably improved[ 11 ]. However, the issue of malnutrition among this demographic remains a serious concern[ 12 ]. Linxia Hui Autonomous Prefecture in Gansu Province faces economic challenges with relatively limited development and this region is inhabited by a significant population of ethnic minorities. Given the distinctive demographic and economic characteristics of Linxia Hui Autonomous Prefecture in Gansu Province, heightened attention should be directed towards monitoring and enhancing the nutritional status, height development, and intellectual development of children and adolescents residing in this region. In this research, the investigation revealed a growth retardation prevalence of 1.2% among middle school students in Linxia Hui Autonomous Prefecture, with slightly higher rates among boys (1.3%) than girls (1.2%). Additionally, the prevalence of emaciation was 15.4%, exhibiting notable gender disparities, with boys at 22.7% and girls at 8.1%. Further breakdown of emaciation indicated moderate wasting at 5.5% and mild wasting at 9.9%. These findings align with prior studies conducted by Dong Yanhui et al[ 13 ], examined child and adolescent development in China over the period spanning 1995 to 2014. Their comprehensive analysis revealed a substantial decline in the prevalence of growth retardation, plummeting from 8.1% to a mere 2.4%. Additionally, the rate of wasting exhibited a noteworthy reduction, decreasing from 7.5–4.1%. These findings underscore the significant improvements in the overall nutritional well-being of children and adolescents in China during this time frame. Preethi and colleagues[ 14 ] in a separate study conducted in 2021, adolescents aged 10 to 16 in Telangana, India, were examined. Their findings revealed a substantial total malnutrition detection rate of 48.5%, with a notable gender disparity: 41.3% among males and 53.6% among females. In contrast, the detection rate of malnutrition among middle school students in Linxia Prefecture was comparatively lower than that observed in the Telangana region of India, which may be associated with the eating factors of the country, in addition, this divergence may have been influenced by the economic level and social difference[ 15 ]. Notably, within Linxia Prefecture, the detection rate of malnutrition was significantly higher among boys as compared to girls. This finding was consistent to the study conducted in Nigeria which reported seemingly high stunting prevalence (74.1%) among boys than adolescent girls (50.7%)[ 16 ]. These comparative insights shed light on the varying nutritional challenges faced by adolescents in different geographic and cultural contexts. Furthermore, within Linxia Prefecture, notable distinctions in the detection rate of malnutrition were observed across different age groups. Among middle school students aged 16 and older (≥ 16), the study identified the highest detection rate of malnutrition, aligning with findings from prior research conducted by Niza[ 17 ] and colleagues. This trend highlights the importance of considering age-specific nutritional interventions and strategies tailored to the distinct needs of students at various stages of adolescence. This study discovered that the prevalence of overweight and obesity among middle school students in the Linxia area was 6.5%, with males comprising 7.0% and females 2.5%. This finding aligns with the research conducted by Dong Yanhui et al[ 13 ]. Their findings indicate that the prevalence of obesity in children and adolescents in China surged from 5.3–20.5% between 1995 and 2014. This is consistent with the research conducted by Preethi et al[ 14 ]. In 2021, the combined detection rates of overweight and obesity among adolescents aged 10–16 in the Telangana region of India were reported at 4.6%. Contrasting this, the 2019 data revealed that the detection rate of overweight and obesity among middle school students in Linxia was lower than that observed in Chinese children and adolescents in 2014. Nevertheless, it was still higher than the corresponding rate in the Telangana region of India. Since the reform and opening up more than 40 years ago, the growth and development of children and adolescents in China have made significant advancements[ 18 ] [ 19 ].In this study, the average height of middle school students in Linxia Prefecture was determined to be 159.3 ± 0.79 cm. When stratified by gender, boys exhibited an average height of 162.0 ± 0.08 cm, whereas girls displayed an average height of 156.7 ± 0.06 cm. Notably, the overall height of girls was observed to be lower than that of boys. This gender-based height difference may be attributed to the inherent dissimilarities in the growth and development patterns between males and females[ 20 ]. Furthermore, these disparities in height development between boys and girls may also have a genetic basis[ 21 ]. Compared with the study by Young Goh et al [22] , the average height of middle school students in Linxia Prefecture appears to be at a lower level(159.3cm vs 164.4 cm). The growth and development of children and adolescents are influenced by various factors, including socioeconomic and cultural factors, dietary intake, maternal nutritional status, trace element deficiency, and environmental factors, among others[ 4 ] [ 23 ] [ 24 ]. Before 2006, local surveys indicated severe iodine deficiency in specific populations, resulting in intellectual disabilities in children and delayed mental development in infants and young children. Socioeconomic and cultural factors play a substantial role in the growth and development of children and adolescents, but their impact on intelligence is gradual and may not be immediately evident. In this study, the Raven test was employed to assess the IQ of middle school students in Linxia Prefecture, revealing an average IQ score of 100.7, which is slightly below the 2005 Chinese average of 103.4[ 25 ]. Studies have demonstrated that IQ scores tend to increase by approximately 3.1 points every decade[ 26 ], the intelligence level of middle school students in Linxia Prefecture was found to be approximately 4.7 points lower than the national average during the same period. Notably, there were significant variations in IQ scores among middle school students in different age groups within the region. The data indicated that younger students tended to have higher IQ scores. This trend might be attributed to the progressive implementation of measures aimed at preventing and treating iodine deficiency disorders through the use of iodized salt in Linxia Prefecture over the years. As awareness of the detrimental effects of iodine deficiency increased, younger middle school students benefited from their mothers having less iodine deficiency during pregnancy and after childbirth, resulting in lower rates of intellectual impairment compared to students whose mothers experienced iodine deficiency during pregnancy. Gender differences in IQ among middle school students in Linxia Prefecture were also observed, which aligns with findings from a study by Dunkel et al.[ 27 ]. It's worth noting that both growth retardation and wasting showed significant associations with IQ in this study. This observation aligns with previous research that has consistently highlighted the connection between malnutrition and intelligence[ 26 ]. The study found that among students with intermediate or higher IQ, the detection rate of growth retardation was 0%. This suggests that students with higher IQs had a notably lower incidence of growth retardation. This aligns with previous research by Adedeji et al.[ 26 ], which demonstrated that malnutrition, including both growth retardation and wasting, significantly raises the likelihood of lower IQ scores by a factor of three. Growth retardation, often indicative of early nutritional deficiencies, can have enduring and irreversible effects on cognition. This is potentially due to chronic nutritional deficits leading to neuropathic changes in the brain, which in turn impact intellectual development[ 28 ]. Indeed, Adede[ 26 ], Akubuilo et al.[ 29 ], and others have suggested that short-term malnutrition may not have a significant impact on intelligence. The existing literature on the mechanisms linking malnutrition to cognitive function and intelligence, which includes considerations of structural changes and genetic modifications in the brain and neural cells, has primarily focused on cases of prolonged malnutrition. Additionally, our study's intriguing finding is that middle school students with overnutrition, including those who were overweight or obese, did not exhibit low IQ scores. This observation suggests a potential positive relationship between overnutrition and IQ, aligning with the findings of Akubuilo et al.[ 29 ]. However, these findings contrast with research conducted in Southeast Asia[ 30 ]. It is plausible that the association between overweight, obesity, and IQ may be influenced by a third variable, such as socio-economic status[ 29 ]. Overnutrition and higher IQ were found to be associated with higher socio-economic levels. This correlation may be attributed to families with higher socio-economic status typically having parents with higher levels of education. Numerous studies have demonstrated a link between parents' educational attainment and children's IQ [26] . Students with higher IQs often excel academically and may spend more time studying, potentially neglecting physical exercise, which could contribute to overweight and obesity. Additionally, children from families with higher economic status tend to have ample food resources, leading to overnutrition and the risk of overweight and obesity. Furthermore, this study identified a positive correlation between height and IQ. Specifically, middle school students with high height development had IQ scores 1.816 times higher than those with low height development and 1.433 times higher than those with moderate height development. This finding aligns with prior research conducted by Maeehew et al.[ 31 ]. It is worth noting that this study does have some limitations. First, this study did not take into account the effects of diet on children and adolescents and some other factors such as environmental factors or genetic predisposition; however, these factors may raise issues that affect different nutritional and health problems in children and adolescents. In future studies, we will further explore the role of these factors in the nutritional status of children and adolescents. Second, this study, as a cross-sectional design, only provided clues to the relationship between nutritional status and IQ; therefore, further studies are needed to validate these relationships. CONCLUSION In summary, the study revealed several key findings among middle school students in Linxia Hui Autonomous Prefecture. There was a slightly elevated rate of malnutrition, and issues related to overweight and obesity were present. Furthermore, the average height among students was relatively low, and their IQ scores were lower than those reported in other regions of China. Additionally, the study identified significant relationships between IQ and various factors including growth retardation, wasting, overnutrition, and height development among middle school students in this region. Hence, as part of efforts to improve nutrition, it is imperative to integrate the distinctive ethnic characteristics and local conditions. This includes implementing health education and promotion programs to disseminate nutritional knowledge, fostering healthy eating habits, encouraging physical activity, modifying unhealthy lifestyles, and ultimately reducing the prevalence of malnutrition, overweight, and obesity. Declarations ACKNOWLEDGEMENTS The authors wish to thank the study participants for their contribution to the research, as well as current and past investigators and staff. The authors would specifically like to thank XiaoDan Huang providing language help and writing assistancefor this paper. AUTHOR CONTRIBUTIONS The authors’ responsibilities were as follows—Yanling Wang, Aiwei HE: designed research; Jing Zhen1, Wei Sun1, Xiulan Fei: conducted research; Qinglin Li, Yanling Wang analyzed data; Qinglin Li, Yanling Wang wrote paper; and all authors: read and approved the final manuscript. FUNDING This work was supported by the Gansu Provincial Science and Technology Program Funded Projects (22JR11RA184) and Gansu Province Health Industry Research Program (GSWSKY2021-008). ETHICS STATEMENT Approved by the Ethics Committee of the Gansu Provincial Center for Disease Control and Prevention. COMPETING INTERESTS The authors declare no competing interests. References JK D, RA S, KL T, AM P, S C, ZS L et al. Nutrition in adolescents: physiology, metabolism, and nutritional needs. Ann N Y Acad Sci 2017 Apr; 1393 (1) : 21-33. https://doi.org/10.1111/nyas.13330. SE C, AE K. Determinants of undernutrition and overnutrition among adolescents in developing. 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Nutr Health 2023 Mar; 29 (1) : 61-69. https://doi.org/10.1177/02601060221090699 Q Z. Multifaceted Interventions for Enhancing Nutritional Status Among Chinese Children and Adolescents. China CDC Wkly 2023 Jun 16; 5 (24) : 525-527. https://doi.org/10.46234/ccdcw2023.101 (NCD-RisC) NRFC. Height and body-mass index trajectories of school-aged children and adolescents. Lancet 2020 Nov 7; 396 (1026) : 1511-1524. https://doi.org/10.1016/S0140-6736(20)31859-6 Y L, S K, M F. Age of onset of a normally timed pubertal growth spurt affects the final height of children. Pediatr Res 2015 Sep; 78 (3) : 351-355. https://doi.org/10.1038/pr.2015.104 YH H, XY W, HY Y, J Z, DP Y, S FG. Increases in Height among Chinese Children and Adolescents by Gender: An Age-Period-Cohort Analysis. Biomed Environ Sci 2021 May 20; 34 (5) : 348-355. https://doi.org/10.3967/bes2021.046 Goh Y-G, Choi S-W, Kim S-Y, Choi J-H. Nutritional status and dietary behavior of North Korean adolescent refugees based on Nutrition Quotient for Korean adolescents: a preliminary study. Korean Journal of Community Nutrition 2023; 28: 1-10. https://doi.org/ http://doi.org/10.5720/kjcn.2023.28.1.1 A M, R D. Severe stunting and its associated factors among children aged 6-59 months in Ethiopia; multilevel ordinal logistic regression model. Ital J Pediatr 2021 Jul 26; 47 (1) : 161. https://doi.org/10.1186/s13052-021-01110-8 Y D, PWC L, B D, Z Z, Y Y, B W et al. Trends in physical fitness, growth, and nutritional status of Chinese children and adolescents: a retrospective analysis of 1·5 million students from six successive national surveys between 1985 and 2014. Lancet Child Adolesc Health 2019 Dec; 3 (12) : 871-880. https://doi.org/10.1016/S2352-4642(19)30302-5 Xiaohui S, Shoujun L, Hongmei S, Shubin Z, Honglian W, Jun Y et al. National iodine deficiency disorder surveillance: a sum up of data in 2005 and an analysis. Chin J Endemiol 2007; 26 (1) : 67-69. https://doi.org/10.3760/cma.j.issn.1000-4955.2007.01.021 Adedeji I, John C, Okolo S, Ebonyi A, Abdu H, Bashir MF. Malnutrition and the Intelligence Quotient of Primary School Pupils in Jos, Nigeria. BJMMR 2017; 21 (2) : 1-13. https://doi.org/10.9734/BJMMR/2017/32504. Dunke CS, Madison G. The possible role of field independence/dependence on developmental sex differences in general intelligence. Intelligence 2022; 91: 101628. https://doi.org/10.1016/j.intell.2022.101628 JR G, ML B-V, Q T, AG R, KI M, WJ C et al. Neurodevelopmental effects of childhood malnutrition: A neuroimaging perspective. Neuroimage 2021 May 1; 213: 117828. https://doi.org/10.1016/j.neuroimage.2021.117828 UC A, KK I, JU O, ON I, AC U, AN I. Nutritional status of primary school children: Association with intelligence quotient and academic performance. Clin Nutr ESPEN 2020 Dec; 40: 208-213. https://doi.org/10.1016/j.clnesp.2020.09.019 Sandjaja, K. PB, N. R, K. LNB, B. B, O. NL et al. Relationship between anthropometric indicators and cognitive performance in Southeast Asian school-aged children. Br J Nutr 2013; 110 (S3) : S57-64. https://doi.org/10.1017/S0007114513002079 Keller MC, Garver-Apgar CE, Wright MJ, Martin NG, Corley RP, Stallings MC et al. The genetic correlation between height and IQ: shared genes or assortative mating? PLoS Genetics 2013; 9 (4) : e1003451. https://doi.org/10.1371/journal.pgen.1003451 Additional Declarations There is NO conflict of interest to disclose. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4002108","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":323040571,"identity":"ce85007d-39f2-4899-bf0b-cdc1a034b3cd","order_by":0,"name":"Yanling Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuUlEQVRIiWNgGAWjYFAC5gaGBAYGOTb25gPEamEEazHm4zmWQIIWIEicJ5GjQJwGgxuJbRIPamzS2xhyGBh+VGwjSkuzQcKxtNw2hrMHGHvO3CasxexGYuODBLbDuW2MfQnMjG3EaWk4kPDvcDobM48B0VoaHyS2HU5gYyNWi/2Zh80GiX1phm08bAkHifKLZHvyMckf32zk5ec/PvjgRwURWhgEEhDsA0SoBwJ+ItWNglEwCkbBCAYApek+tHEZs5IAAAAASUVORK5CYII=","orcid":"","institution":"Gansu Provincial Center for Disease Prevention and Control ","correspondingAuthor":true,"prefix":"","firstName":"Yanling","middleName":"","lastName":"Wang","suffix":""},{"id":323040572,"identity":"32032a3f-7b97-4158-8159-2a642503136d","order_by":1,"name":"Qinglin Li","email":"","orcid":"","institution":"Gansu Provincial Center for Disease Prevention and Control ","correspondingAuthor":false,"prefix":"","firstName":"Qinglin","middleName":"","lastName":"Li","suffix":""},{"id":323040573,"identity":"bce33db7-7bee-4d5c-9608-540fb1d0c8a0","order_by":2,"name":"Jing Zhen","email":"","orcid":"","institution":"Gansu Provincial Center for Disease Prevention and Control ","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Zhen","suffix":""},{"id":323040574,"identity":"89134d42-83a2-48af-9da7-4f52d776f8f0","order_by":3,"name":"Wei Sun","email":"","orcid":"","institution":"Gansu Provincial Center for Disease Prevention and Control ","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Sun","suffix":""},{"id":323040575,"identity":"819fe7d0-498e-40e4-b681-d56d4b1f900c","order_by":4,"name":"Aiwei He","email":"","orcid":"","institution":"Gansu Provincial Center for Disease Prevention and Control ","correspondingAuthor":false,"prefix":"","firstName":"Aiwei","middleName":"","lastName":"He","suffix":""},{"id":323040576,"identity":"85a2796d-23fb-42e8-9695-126eef7221b2","order_by":5,"name":"Xiaonan Zhu","email":"","orcid":"","institution":"Gansu Provincial Center for Disease Prevention and Control ","correspondingAuthor":false,"prefix":"","firstName":"Xiaonan","middleName":"","lastName":"Zhu","suffix":""}],"badges":[],"createdAt":"2024-03-01 05:05:40","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4002108/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4002108/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":65917313,"identity":"4b3f5e60-ec8a-4286-84fe-cb1a777d1db3","added_by":"auto","created_at":"2024-10-04 11:03:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1126128,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4002108/v1/ba057a9f-f851-48b9-85c7-8eff53ccb9c0.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.","formattedTitle":"Exploring the Link between Physiological Development and Intellectual Proficiency among Middle School Students in Linxia Hui Autonomous Prefecture, Gansu Province, China","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThe secondary school period is a critical phase of pubertal growth and development, ranking second in significance only to infancy but extending over a more protracted duration. Consequently, the nutritional requisites during this pivotal epoch are anticipated to surpass those encountered in any other developmental stage. Hence, the paramount importance of securing adequate nutrition remains pivotal in the endeavor to realize the full spectrum of growth potential[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In many developing countries, adolescent stunting, underweight, and micronutrient deficiencies were often result from a combination of malnutrition in early childhood and an inadequate diet to meet the intense nutritional requirements for rapid adolescent growth[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. According to a 2020 World Health Organization report, approximately 47\u0026nbsp;million children under 5 years old worldwide suffered from wasting, while around 144\u0026nbsp;million were affected by stunting[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Furthermore, an estimated 200\u0026nbsp;million school-aged children globally grappled with malnourishment, with malnutrition implicated in approximately 45% of child mortality cases[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Children's capacities evolve through intricate interactions between their developing brains and environmental factors during the formative years[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], Previous investigations conducted in Northwest China have underscored the challenges posed by disadvantaged geographical environments and lower economic status in this region[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. As a multi-ethnic enclave in Northwest China and a focal point of national poverty alleviation efforts, Linxia Hui Autonomous Prefecture boasts distinct residential settings, cultural backgrounds, and dietary patterns compared to other regions. To comprehensively understand the growth and cognitive aptitude of middle school students aged 11 to 18 in this unique context, this study conducted an assessment in 2019, through a survey of the nutritional status and intelligence proficiency of local secondary school students. The aim was to provide a foundational basis for enhancing the growth and intellectual development of local middle school students.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSurvey object and sampling method\u003c/h2\u003e \u003cp\u003eIn 2019, a comprehensive survey was undertaken, involving a total cohort of 1682 students. These students were selected from 8 counties (cities) within the administrative purview of Linxia Hui Autonomous Prefecture, Gansu Province, China. The geographical regions encompassed Linxia City, Linxia County, Yongjing County, Dongxiang County, Guanghe County, Kangle County, Hezheng County, and Jishishan County.The selection process adhered to the principles of convenience sampling, encompassing 2 to 5 townships in each county (city) and 1 to 2 secondary schools in each township.It is noteworthy that this study received ethical clearance from the Ethics Committee of the Gansu Provincial Center for Disease Control and Prevention (Approval No. [031], 2021). Furthermore, it is pertinent to mention that all participating students provided informed consent through the signing of consent forms, thereby ensuring their voluntary and informed participation in the study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eSurvey content and method\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eMeasurement of physical indicators\u003c/h2\u003e \u003cp\u003eThe gender and age of all subjects were meticulously recorded, and their height was assessed following a standardized procedure, with precision to the nearest 0.1 cm. Weight measurements were conducted using a consistent type of weight scale, with subjects removing their shoes to ensure accuracy, and measurements were recorded with precision to the nearest 0.1 kg.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eEvaluation of nutritional status\u003c/h2\u003e \u003cp\u003eBody mass index (BMI) serves as an objective indicator of growth and development and represents a commonly employed metric for assessing nutritional status. BMI calculations were derived from height and weight data, utilizing the formula: BMI\u0026thinsp;=\u0026thinsp;weight (kg)/height \u003csup\u003e2\u003c/sup\u003e (m\u003csup\u003e2\u003c/sup\u003e). The assessment of growth retardation and wasting, which includes both moderate and mild forms of wasting, was conducted in accordance with the guidelines outlined in the \u0026lsquo;Screening for Malnutrition in School-Age Children and Adolescents\u0026rsquo; (WS/T456-2014)[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Furthermore, the determination of overweight and obesity status was executed following the protocols stipulated in the \u0026lsquo;Screening for Overweight and Obesity in School-Age Children and Adolescents\u0026rsquo; (WS/T586-2018)[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eHeight development grade evaluation\u003c/h2\u003e \u003cp\u003eThe assessment of height development grades followed the guidelines outlined in the \u0026lsquo;Standard for height level classification among children and adolescents aged 7\u0026thinsp;~\u0026thinsp;18 years\u0026rsquo; (WS/T612-2018)[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. the height development levels were categorized into five distinct tiers, as follows: height\u0026thinsp;\u0026lt;\u0026thinsp;\u0026minus;\u0026thinsp;2SD (standard deviations) was classified as inferior; -height\u0026thinsp;\u0026ge;\u0026thinsp;\u0026minus;\u0026thinsp;2SD and \u0026lt;\u0026thinsp;\u0026minus;\u0026thinsp;1SD was categorized as lower-middle; height\u0026thinsp;\u0026ge;\u0026thinsp;\u0026minus;\u0026thinsp;1SD and \u0026le;\u0026thinsp;+\u0026thinsp;1SD was labeled as middle; height\u0026thinsp;\u0026gt;\u0026thinsp;+\u0026thinsp;1SD and \u0026le;\u0026thinsp;+\u0026thinsp;2SD was considered middle-upper; Height\u0026thinsp;\u0026gt;\u0026thinsp;+\u0026thinsp;2SD was superior (Note: SD was standard deviation). It is important to note that the classification criteria were consistent across all age groups.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eIQ test\u003c/h2\u003e \u003cp\u003eThe assessment of intelligence among the sampled students was conducted using the second Revised version of the Combined Raven\u0026rsquo;s Test (CRT-C2) designed for children in China. The administration of this test was overseen by provincial personnel who had undergone national training and possessed qualifications, holding the Raven Psychological Test Certificate. Intelligence scores were categorized into seven grades[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], as follows: very excellent (IQ\u0026thinsp;\u0026ge;\u0026thinsp;130), excellent (120\u0026thinsp;~\u0026thinsp;129), upper middle (110\u0026thinsp;~\u0026thinsp;119), middle (90\u0026thinsp;~\u0026thinsp;109), lower middle (80\u0026thinsp;~\u0026thinsp;89), marginal (70\u0026thinsp;~\u0026thinsp;79), and low (\u0026le;\u0026thinsp;69). This comprehensive classification system allowed for a nuanced evaluation of the students' cognitive abilities.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eQuality control\u003c/h2\u003e \u003cp\u003eThe investigation efforts were executed by a team of provincially trained professional and technical personnel. The consistency of investigators was maintained throughout the entire process, with strict adherence to the pertinent technical guidelines. Each stage of the investigation, spanning from training and sample selection to fieldwork, data collection, analysis, and compilation, was meticulously overseen by dedicated personnel with clearly defined responsibilities. In the realm of physical measurements, height and weight were ascertained using standardized measuring instruments to ensure uniformity and precision. Similarly, for intelligence assessments, testers adhered to predefined standards and conducted the tests conscientiously. To enhance data integrity, a consistent numbering system for survey data was implemented, complemented by real-time verification and dual data entry procedures.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis for this study was conducted using SPSS version 20.0 Descriptive statistics for count data were presented in terms of case numbers and percentages [n(%)], Chi-square test was employed. Additionally, to gauge the strength of the association between nutritional status and IQ, ordered logistic regression was utilized.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eDemographic Profile of Middle School Students in Linxia Hui Autonomous Prefecture\u003c/h2\u003e\n \u003cp\u003eIn this study, a comprehensive survey was conducted involving a total of 1682 middle school students. Of this cohort, 835 students (49.6%) were male, while 847 students (50.4%) were female. The age distribution ranged from 11 to 18 years, with an average age of (14.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.961) years for the entire sample.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eNutrition Status Assessment of Middle School Students in Linxia Hui Autonomous Prefecture\u003c/h2\u003e\n \u003cp\u003eAs presented in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, the detection rate of growth retardation displaying statistically significant differences across age groups(\u003cem\u003e\u0026chi;\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;58.631, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Notably, there were no reported cases of malnutrition (moderate wasting and mild wasting) among 11-year-old middle school students. Furthermore, significant disparities were noted in the overall nutritional status of middle school students when considering gender (\u003cem\u003e\u0026chi;\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;77.977, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and age (\u003cem\u003e\u0026chi;\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;46.369, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), as detailed in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003cbr\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eGrowth retardation of participants [n (%)]\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eGrowth retardation\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026chi;\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGirls\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e835\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11(1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e824 (98.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.830\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.487\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBoys\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e847\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e837 (98.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e58.631\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e525\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e524 (99.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e716\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e713 (96.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e263\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e253 (91.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (8.4))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76 (98.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1682\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1661 (98.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eNutritional status of participants [n (%)]\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"12\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eBMI ( \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\overline{\\text{x}}\\pm \\text{s}\\))\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eWasting\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eOvernutrition\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026chi;\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eModerate wasting\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMild wasting\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSubtotal\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOverweight\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eObesity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSubtotal\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGirls\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e835\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58 (6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e132 (15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e190 (22.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e587 (70.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38 (4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58 (7.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e77.977\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBoys\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e847\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34 (4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69 (8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e727 (85.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51 (2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e46.369\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76 (89.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e525\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 (8.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64 (12.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e432 (82.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e716\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36 (5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83 (11.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e119 (16.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e540 (75.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37 (5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57 (8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e263\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26 (9.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25 (9.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51 (19.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e199 (75.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (22.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59 (71.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1682\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92 (5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e167 (9.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e259 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1314 (78.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70 (4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e109 (6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003eHeight Development Assessment among Middle School Students in Linxia Hui Autonomous Prefecture\u003c/h2\u003e\n \u003cp\u003eAs delineated in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, the mean height of middle school students in Linxia Prefecture averaged at 159.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79 cm. This disparity in height development between male and female middle school students was statistically significant (\u003cem\u003e\u0026chi;\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;28.746, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Furthermore, the middle school students in the region have statistically significant differences in height development across different age group (\u003cem\u003e\u0026chi;\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;144.209,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Notably, among 11-year-old students, there were no reported cases of height development classified as inferior or lower middle. Similarly, among high school students aged\u0026thinsp;\u0026ge;\u0026thinsp;16, no instances of height development classified as superior levels were identified.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eHeight development of participants [n (%)]\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"10\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eHeight (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\overline{\\text{x}}\\pm \\text{s}\\))\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eHeight Development\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026chi;\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eInferior\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLower middle\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUpper middle\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSuperior\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"10\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGirls\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e835\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e162.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62 (7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e148 (17.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e530 (63.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e81 (9.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e28.746\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBoys\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e847\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e156.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e118 (13.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e580 (68.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e101 (11.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25 (19.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e155.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (30.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e144.209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e156.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53 (62.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (22.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (8.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e525\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e157.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65 (12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e386 (73.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53 (10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (12.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e716\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e160.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34 (4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e115 (16.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e481 (67.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74 (10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e263\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e160.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53 (20.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e150 (57.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26 (9.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e160.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (15.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (33.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (42.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (8.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1682\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e159.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85 (5.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e266 (15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1110 (66.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e182 (10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eIQ of participants [n (%)]\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"12\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\overline{\\text{x}}\\pm \\text{s}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003eIQ\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026chi;\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLow(\u0026le;\u0026thinsp;69)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMarginal\u003c/p\u003e\n \u003cp\u003e(70～79)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLower middle\u003c/p\u003e\n \u003cp\u003e(80～89)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003cp\u003e(90～109)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUpper middle\u003c/p\u003e\n \u003cp\u003e(110～119)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eExcellent\u003c/p\u003e\n \u003cp\u003e(120～129)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVery excellent\u003c/p\u003e\n \u003cp\u003e(\u0026ge;\u0026thinsp;130)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGirls\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e835\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99.85\u0026thinsp;\u0026plusmn;\u0026thinsp;16.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75 (9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e436 (52.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e97 (11.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74 (8.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e26.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBoys\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e847\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e101.61\u0026thinsp;\u0026plusmn;\u0026thinsp;17.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66 (7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96 (11.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e374 (44.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e169 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80 (9.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34 (4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e114.40\u0026thinsp;\u0026plusmn;\u0026thinsp;8.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (30.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (30.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e498.959\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e108.79\u0026thinsp;\u0026plusmn;\u0026thinsp;12.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41 (48.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (28.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (11.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e525\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e107.36\u0026thinsp;\u0026plusmn;\u0026thinsp;14.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e255 (48.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e111 (21.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76 (14.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36 (6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e716\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e102.33\u0026thinsp;\u0026plusmn;\u0026thinsp;14.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38 (5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89 (12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e377 (52.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e118 (16.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62 (8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e263\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86.47\u0026thinsp;\u0026plusmn;\u0026thinsp;16.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 (8.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e73 (27.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45 (17.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e111 (42.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80.35\u0026thinsp;\u0026plusmn;\u0026thinsp;16.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (19.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (24.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (27.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (27.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1682\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100.73\u0026thinsp;\u0026plusmn;\u0026thinsp;17.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49 (2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e141 (8.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e196 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e810 (48.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e266 (15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e154 (9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66 (3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003eCognitive Intelligence (IQ) Status Among Middle School Students in Linxia Hui Autonomous Prefecture\u003c/h2\u003e\n \u003cp\u003eThe mean IQ score for middle school students in Linxia Hui Autonomous Prefecture averaged at (100.7\u0026thinsp;\u0026plusmn;\u0026thinsp;17.02). Significant disparities were observed in IQ values concerning gender distribution, with female students exhibiting higher IQ scores than their male counterparts(\u003cem\u003e\u0026chi;\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;26.1, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Additionally, IQ scores demonstrated variance across different age groups, with younger students achieving higher IQ score (\u003cem\u003e\u0026chi;\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;498.959, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), as shown in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eComprehensive Assessment of Nutritional status, height development level, and IQ of middle school students in Linxia Hui Autonomous Prefecture\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAs illustrated in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e, there were no instances of middle school students with growth retardation who achieved IQ scores at or above the middle level. Similarly, there were no overweight or obese middle school students with low IQ scores. Furthermore, no middle school students with excellent height development exhibited low IQ scores, and there were no middle school students with inferior height development who attained excellent IQ scores.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eNutritional status, height development, and IQ of participants\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"11\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003eIQ\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026chi;\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLow (\u0026le;\u0026thinsp;69)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMarginal\u003c/p\u003e\n \u003cp\u003e(70～79)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLower middle\u003c/p\u003e\n \u003cp\u003e(80～89)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003cp\u003e(90～109)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUpper middle\u003c/p\u003e\n \u003cp\u003e(110～119)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eExcellent\u003c/p\u003e\n \u003cp\u003e(120～129)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVery excellent\u003c/p\u003e\n \u003cp\u003e(\u0026ge;\u0026thinsp;130)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGrowth retardation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (28.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (9.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (42.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e35.693\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1661\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e135 (8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e194 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e801 (48.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e266 (16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e154 (9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66 (4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNutritional status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMild wasting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 (46.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e78.729\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMild wasting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 (13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92 (55.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (14.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38 (2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e109 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e150 (11.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e622 (47.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e219 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e119 (9.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51 (3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOverweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (18.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (12.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (15.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eObesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (5.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (48.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (17.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eHeight Development\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInferior\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (8.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (11.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (21.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42 (49.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e101.165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLower middle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e266\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38 (14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e136 (51.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (10.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80 (7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e129 (11.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e542 (48.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e188 (16.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e106 (9.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 (3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUpper middle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17 (9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (40.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (13.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (10.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSuperior\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (41.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (38.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (12.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1682\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49 (2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e141 (8.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e196 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e810 (48.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e266 (15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e154 (9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66 (3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eOrdered Logistic Regression Analysis of the Association Between Nutritional Status and IQ among Middle School Students in Linxia Hui Autonomous Prefecture\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe nutritional status was categorized into three distinct grades: wasting, overnutrition and normal, while height development was classified into lower, middle and upper grades. Meanwhile, the cognitive intelligence (IQ) levels were dependent variable across seven grades. Ordered logistic regression analysis was employed, utilizing growth retardation, nutritional status, and height development grade as independent variables. The results, as depicted in Table \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e, revealed that growth retardation (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.675, 95%\u003cem\u003eCI\u003c/em\u003e 1.189\u0026thinsp;~\u0026thinsp;6.018, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), wasting(\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.683, 95%\u003cem\u003eCI\u003c/em\u003e 1.016\u0026thinsp;~\u0026thinsp;2.561, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), overnutrition (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.748, 95%\u003cem\u003eCI\u003c/em\u003e 1.214\u0026thinsp;~\u0026thinsp;2.516, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), low height development (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.816, 95%\u003cem\u003eCI\u003c/em\u003e 1.313\u0026thinsp;~\u0026thinsp;2.511, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and middle height development (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.433, 95%\u003cem\u003eCI\u003c/em\u003e 1.095\u0026thinsp;~\u0026thinsp;1.875, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were identified as risk factors for middle school students in this region. Specifically, middle school students without growth retardation in their nutritional status exhibited IQ scores 2.675 times higher than those of their counterparts with growth retardation. Moreover, students with normal nutritional status demonstrated IQ scores 1.683 times higher than those with wasting and 1.748 times higher than those with overnutrition. Additionally, students with high height development displayed IQ scores 1.816 times and 1.433 times higher than those with low and moderate height development, respectively .\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eOrdered logistic regression analysis of the relationship between nutritional status, height grade, and IQ\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"9\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eWald\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eOR\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e95%\u003cem\u003eCI\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eGrowth retardation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.984\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.414\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.657\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.017\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.675\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eNutritional status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWasting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.521\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.356\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.015\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.683\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.561\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOvernutrition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.633\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.332\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.642\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.748\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.516\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eHeight development\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLower\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.597\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.000\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.816\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.313\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.511\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.879\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.009\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.433\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.095\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.875\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUpper\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"9\"\u003e\n \u003cp\u003eNote: \u003csup\u003e*\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e \u0026lt;0.05;\u003csup\u003e**\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e \u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eDespite the continuous economic development, the nutritional status of children and adolescents in China has notably improved[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, the issue of malnutrition among this demographic remains a serious concern[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Linxia Hui Autonomous Prefecture in Gansu Province faces economic challenges with relatively limited development and this region is inhabited by a significant population of ethnic minorities. Given the distinctive demographic and economic characteristics of Linxia Hui Autonomous Prefecture in Gansu Province, heightened attention should be directed towards monitoring and enhancing the nutritional status, height development, and intellectual development of children and adolescents residing in this region.\u003c/p\u003e \u003cp\u003eIn this research, the investigation revealed a growth retardation prevalence of 1.2% among middle school students in Linxia Hui Autonomous Prefecture, with slightly higher rates among boys (1.3%) than girls (1.2%). Additionally, the prevalence of emaciation was 15.4%, exhibiting notable gender disparities, with boys at 22.7% and girls at 8.1%. Further breakdown of emaciation indicated moderate wasting at 5.5% and mild wasting at 9.9%. These findings align with prior studies conducted by Dong Yanhui et al[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], examined child and adolescent development in China over the period spanning 1995 to 2014. Their comprehensive analysis revealed a substantial decline in the prevalence of growth retardation, plummeting from 8.1% to a mere 2.4%. Additionally, the rate of wasting exhibited a noteworthy reduction, decreasing from 7.5\u0026ndash;4.1%. These findings underscore the significant improvements in the overall nutritional well-being of children and adolescents in China during this time frame. Preethi and colleagues[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] in a separate study conducted in 2021, adolescents aged 10 to 16 in Telangana, India, were examined. Their findings revealed a substantial total malnutrition detection rate of 48.5%, with a notable gender disparity: 41.3% among males and 53.6% among females. In contrast, the detection rate of malnutrition among middle school students in Linxia Prefecture was comparatively lower than that observed in the Telangana region of India, which may be associated with the eating factors of the country, in addition, this divergence may have been influenced by the economic level and social difference[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Notably, within Linxia Prefecture, the detection rate of malnutrition was significantly higher among boys as compared to girls. This finding was consistent to the study conducted in Nigeria which reported seemingly high stunting prevalence (74.1%) among boys than adolescent girls (50.7%)[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. These comparative insights shed light on the varying nutritional challenges faced by adolescents in different geographic and cultural contexts. Furthermore, within Linxia Prefecture, notable distinctions in the detection rate of malnutrition were observed across different age groups. Among middle school students aged 16 and older (\u0026ge;\u0026thinsp;16), the study identified the highest detection rate of malnutrition, aligning with findings from prior research conducted by Niza[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] and colleagues. This trend highlights the importance of considering age-specific nutritional interventions and strategies tailored to the distinct needs of students at various stages of adolescence.\u003c/p\u003e \u003cp\u003eThis study discovered that the prevalence of overweight and obesity among middle school students in the Linxia area was 6.5%, with males comprising 7.0% and females 2.5%. This finding aligns with the research conducted by Dong Yanhui et al[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Their findings indicate that the prevalence of obesity in children and adolescents in China surged from 5.3\u0026ndash;20.5% between 1995 and 2014. This is consistent with the research conducted by Preethi et al[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In 2021, the combined detection rates of overweight and obesity among adolescents aged 10\u0026ndash;16 in the Telangana region of India were reported at 4.6%. Contrasting this, the 2019 data revealed that the detection rate of overweight and obesity among middle school students in Linxia was lower than that observed in Chinese children and adolescents in 2014. Nevertheless, it was still higher than the corresponding rate in the Telangana region of India.\u003c/p\u003e \u003cp\u003eSince the reform and opening up more than 40 years ago, the growth and development of children and adolescents in China have made significant advancements[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].In this study, the average height of middle school students in Linxia Prefecture was determined to be 159.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79 cm. When stratified by gender, boys exhibited an average height of 162.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08 cm, whereas girls displayed an average height of 156.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 cm. Notably, the overall height of girls was observed to be lower than that of boys. This gender-based height difference may be attributed to the inherent dissimilarities in the growth and development patterns between males and females[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Furthermore, these disparities in height development between boys and girls may also have a genetic basis[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Compared with the study by Young Goh et al\u003csup\u003e[22]\u003c/sup\u003e, the average height of middle school students in Linxia Prefecture appears to be at a lower level(159.3cm vs 164.4 cm).\u003c/p\u003e \u003cp\u003eThe growth and development of children and adolescents are influenced by various factors, including socioeconomic and cultural factors, dietary intake, maternal nutritional status, trace element deficiency, and environmental factors, among others[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Before 2006, local surveys indicated severe iodine deficiency in specific populations, resulting in intellectual disabilities in children and delayed mental development in infants and young children. Socioeconomic and cultural factors play a substantial role in the growth and development of children and adolescents, but their impact on intelligence is gradual and may not be immediately evident. In this study, the Raven test was employed to assess the IQ of middle school students in Linxia Prefecture, revealing an average IQ score of 100.7, which is slightly below the 2005 Chinese average of 103.4[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Studies have demonstrated that IQ scores tend to increase by approximately 3.1 points every decade[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], the intelligence level of middle school students in Linxia Prefecture was found to be approximately 4.7 points lower than the national average during the same period. Notably, there were significant variations in IQ scores among middle school students in different age groups within the region. The data indicated that younger students tended to have higher IQ scores. This trend might be attributed to the progressive implementation of measures aimed at preventing and treating iodine deficiency disorders through the use of iodized salt in Linxia Prefecture over the years. As awareness of the detrimental effects of iodine deficiency increased, younger middle school students benefited from their mothers having less iodine deficiency during pregnancy and after childbirth, resulting in lower rates of intellectual impairment compared to students whose mothers experienced iodine deficiency during pregnancy.\u003c/p\u003e \u003cp\u003eGender differences in IQ among middle school students in Linxia Prefecture were also observed, which aligns with findings from a study by Dunkel et al.[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. It's worth noting that both growth retardation and wasting showed significant associations with IQ in this study. This observation aligns with previous research that has consistently highlighted the connection between malnutrition and intelligence[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The study found that among students with intermediate or higher IQ, the detection rate of growth retardation was 0%. This suggests that students with higher IQs had a notably lower incidence of growth retardation. This aligns with previous research by Adedeji et al.[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], which demonstrated that malnutrition, including both growth retardation and wasting, significantly raises the likelihood of lower IQ scores by a factor of three. Growth retardation, often indicative of early nutritional deficiencies, can have enduring and irreversible effects on cognition. This is potentially due to chronic nutritional deficits leading to neuropathic changes in the brain, which in turn impact intellectual development[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Indeed, Adede[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], Akubuilo et al.[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], and others have suggested that short-term malnutrition may not have a significant impact on intelligence. The existing literature on the mechanisms linking malnutrition to cognitive function and intelligence, which includes considerations of structural changes and genetic modifications in the brain and neural cells, has primarily focused on cases of prolonged malnutrition.\u003c/p\u003e \u003cp\u003eAdditionally, our study's intriguing finding is that middle school students with overnutrition, including those who were overweight or obese, did not exhibit low IQ scores. This observation suggests a potential positive relationship between overnutrition and IQ, aligning with the findings of Akubuilo et al.[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. However, these findings contrast with research conducted in Southeast Asia[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. It is plausible that the association between overweight, obesity, and IQ may be influenced by a third variable, such as socio-economic status[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Overnutrition and higher IQ were found to be associated with higher socio-economic levels. This correlation may be attributed to families with higher socio-economic status typically having parents with higher levels of education. Numerous studies have demonstrated a link between parents' educational attainment and children's IQ\u003csup\u003e[26]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eStudents with higher IQs often excel academically and may spend more time studying, potentially neglecting physical exercise, which could contribute to overweight and obesity. Additionally, children from families with higher economic status tend to have ample food resources, leading to overnutrition and the risk of overweight and obesity. Furthermore, this study identified a positive correlation between height and IQ. Specifically, middle school students with high height development had IQ scores 1.816 times higher than those with low height development and 1.433 times higher than those with moderate height development. This finding aligns with prior research conducted by Maeehew et al.[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIt is worth noting that this study does have some limitations. First, this study did not take into account the effects of diet on children and adolescents and some other factors such as environmental factors or genetic predisposition; however, these factors may raise issues that affect different nutritional and health problems in children and adolescents. In future studies, we will further explore the role of these factors in the nutritional status of children and adolescents. Second, this study, as a cross-sectional design, only provided clues to the relationship between nutritional status and IQ; therefore, further studies are needed to validate these relationships.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eIn summary, the study revealed several key findings among middle school students in Linxia Hui Autonomous Prefecture. There was a slightly elevated rate of malnutrition, and issues related to overweight and obesity were present. Furthermore, the average height among students was relatively low, and their IQ scores were lower than those reported in other regions of China. Additionally, the study identified significant relationships between IQ and various factors including growth retardation, wasting, overnutrition, and height development among middle school students in this region. Hence, as part of efforts to improve nutrition, it is imperative to integrate the distinctive ethnic characteristics and local conditions. This includes implementing health education and promotion programs to disseminate nutritional knowledge, fostering healthy eating habits, encouraging physical activity, modifying unhealthy lifestyles, and ultimately reducing the prevalence of malnutrition, overweight, and obesity.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEDGEMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors wish to thank the study participants for their\u0026nbsp;contribution to the research, as well as current and past\u0026nbsp;investigators and staff. The authors would specifically like to\u0026nbsp;thank\u0026nbsp;XiaoDan Huang\u0026nbsp;providing language help\u0026nbsp;and\u0026nbsp;writing assistancefor this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAUTHOR CONTRIBUTIONS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors\u0026rsquo; responsibilities were as follows\u0026mdash;Yanling Wang, Aiwei HE: designed research; Jing Zhen1, Wei Sun1,\u0026nbsp;Xiulan Fei: conducted research; Qinglin Li, Yanling Wang analyzed data; Qinglin Li, Yanling Wang wrote paper; and all authors: read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFUNDING\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Gansu Provincial Science and Technology Program Funded Projects (22JR11RA184) and Gansu Province Health Industry Research Program (GSWSKY2021-008).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eETHICS STATEMENT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eApproved by the\u0026nbsp;Ethics Committee of the Gansu Provincial Center for Disease Control and Prevention.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCOMPETING INTERESTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eJK D, RA S, KL T, AM P, S C, ZS L\u003cem\u003e et al.\u003c/em\u003e Nutrition in adolescents: physiology, metabolism, and nutritional needs. \u003cem\u003eAnn N Y Acad Sci \u003c/em\u003e2017 Apr; \u003cstrong\u003e1393\u003c/strong\u003e(1)\u003cstrong\u003e: \u003c/strong\u003e21-33. https://doi.org/10.1111/nyas.13330.\u003c/li\u003e\n\u003cli\u003eSE C, AE K. 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NL\u003cem\u003e et al.\u003c/em\u003e Relationship between anthropometric indicators and cognitive performance in Southeast Asian school-aged children. \u003cem\u003eBr J Nutr \u003c/em\u003e2013; \u003cstrong\u003e110\u003c/strong\u003e(S3)\u003cstrong\u003e: \u003c/strong\u003eS57-64. https://doi.org/10.1017/S0007114513002079\u003c/li\u003e\n\u003cli\u003eKeller MC, Garver-Apgar CE, Wright MJ, Martin NG, Corley RP, Stallings MC\u003cem\u003e et al.\u003c/em\u003e The genetic correlation between height and IQ: shared genes or assortative mating? \u003cem\u003ePLoS Genetics \u003c/em\u003e2013; \u003cstrong\u003e9\u003c/strong\u003e(4)\u003cstrong\u003e: \u003c/strong\u003ee1003451. https://doi.org/10.1371/journal.pgen.1003451\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4002108/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4002108/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eOBJECTIVES: \u003c/strong\u003eIs there a correlation between the growth trajectory of middle school students and their intelligence proficiency.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMETHODS: \u003c/strong\u003eA cross-sectional survey was conducted in 2019, involving a total cohort of 1682 students.This survey assess their growth and development status by measuring height and weight and calculating body mass index (BMI). The intelligence of the sampled students was evaluated using the second revision of the Chinese Combined Raven Test (CRT-C2). Ordered logistic regression analysis was employed to comprehensively explore the relationship between their growth and developmental status and IQ.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRESULTS:\u003c/strong\u003e This height disparity between male and female was statistically significant (\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e = 28.746, \u003cem\u003ep\u003c/em\u003e = 0.000). Gender-based differences were observed in IQ scores, with girls outscoring boys (\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e = 26.1, \u003cem\u003ep\u003c/em\u003e = 0.000). Younger students exhibited higher IQ scores (\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e =498.959, \u003cem\u003ep\u003c/em\u003e = 0.000). Further analysis demonstrated that growth retardation (\u003cem\u003eOR \u003c/em\u003e= 2.675, 95%\u003cem\u003eCI\u003c/em\u003e 1.189~6.018, \u003cem\u003ep \u003c/em\u003e= 0.017), wasting(\u003cem\u003eOR \u003c/em\u003e= 1.683, 95%\u003cem\u003eCI\u003c/em\u003e 1.016~2.561, \u003cem\u003ep \u003c/em\u003e= 0.015), overnutrition (\u003cem\u003eOR \u003c/em\u003e= 1.748, 95%\u003cem\u003eCI\u003c/em\u003e 1.214~2.516, \u003cem\u003ep \u003c/em\u003e= 0.003), low height development (\u003cem\u003eOR\u003c/em\u003e=1.816, 95%\u003cem\u003eCI\u003c/em\u003e 1.313~2.511, \u003cem\u003ep \u003c/em\u003e= 0.000) and middle height development (\u003cem\u003eOR \u003c/em\u003e= 1.433, 95%\u003cem\u003eCI\u003c/em\u003e 1.095~1.875, \u003cem\u003ep \u003c/em\u003e= 0.009) were identified as risk factors for middle school students in this region.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCONCLUSION: \u003c/strong\u003eThe research highlights significant that growth retardation, wasting, overnutrition , low and middle height development were detrimental to intellectual development among middle school students in the region.\u003c/p\u003e","manuscriptTitle":"Exploring the Link between Physiological Development and Intellectual Proficiency among Middle School Students in Linxia Hui Autonomous Prefecture, Gansu Province, China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-30 09:29:11","doi":"10.21203/rs.3.rs-4002108/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1909e4b3-4f79-4f8f-92b7-3fdc218dce30","owner":[],"postedDate":"July 30th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":34163492,"name":"Health sciences/Risk factors"},{"id":34163493,"name":"Health sciences/Health care/Nutrition"}],"tags":[],"updatedAt":"2024-10-04T10:55:49+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-30 09:29:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4002108","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4002108","identity":"rs-4002108","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}