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Analysis of undernutrition and associated factors among left-behind and non-left-behind primary and secondary school students in the Nutrition Improvement Program areas in central and western China
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Xin HU1, Wenbin WANG1, Wei CAO1, 2, Hongliang WANG1, Mulei CHEN3, Yao LIU4, Titi YANG1, Hui PAN1, Ruihe LUO1, Jianfen ZHANG1, Qian ZHANG1, 2, Juan XU1
Chinese Journal of School Health | 2026, 47(3) : 327 - 331
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Chinese Journal of School Health | 2026, 47(3): 327-331
Student Nutrition
Analysis of undernutrition and associated factors among left-behind and non-left-behind primary and secondary school students in the Nutrition Improvement Program areas in central and western China
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Xin HU1, Wenbin WANG1, Wei CAO1, 2, Hongliang WANG1, Mulei CHEN3, Yao LIU4, Titi YANG1, Hui PAN1, Ruihe LUO1, Jianfen ZHANG1, Qian ZHANG1, 2, Juan XU1
Affiliations
  • National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
Published: 2026-03-25 doi: 10.16835/j.cnki.1000-9817.2026094
Outline
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Objective

To investigate the prevalence of undernutrition and its associated factors among left-behind and non-left-behind primary and secondary school students in the Nutrition Improvement Program for Rural Compulsory Education Students (NIPRCES) areas of central and western China, so as to provide evidence for improving the nutritional status of children and adolescents.

Methods

A survey was conducted among 123 782 students selected by random cluster sampling method in grades 3-9 from NIPRCES in central (Hebei, Shanxi, Heilongjiang, Jilin, Anhui, Jiangxi, Henan, Hunan, Hubei, and Hainan) and western (Gansu, Guangxi, Inner Mongolia, Ningxia, Tibet, Shaanxi, Guizhou, Sichuan, Xinjiang, the Xinjiang Production and Construction Corps, Yunnan, Qinghai, and Chongqing) China in 2023. Anthropometric measurements and questionnaires were used to assess nutritional and dietary status. The prevalence of undernutrition was compared between left-behind and non-left-behind students by Chi-square test, and associated factors were analyzed by three-level Logistic mixed effects model.

Results

The prevalence of undernutrition was 8.5% (4 326) in left-behind students and 8.1% (5 905) in non-left-behind students. Three-level Logistic mixed-effect model analysis showed that whether left-behind or non-left-behind, the undernutrition rates of primary and secondary students in western regions were higher than those of students in central regions [OR(95%CI)=1.72(1.57-1.87), 2.25(2.07-2.43)]; the undernutrition risk was lower for those whose fathers had a cultural level of high school or above [OR(95%CI)=0.69(0.62-0.77), 0.90(0.82-0.98)] or junior high school [OR(95%CI)=0.72(0.66-0.79), 0.92(0.85-0.99)] compared to those with primary school or below; picky eating or selective eating increased the risk of undernutrition [OR(95%CI)=2.36(2.07-2.68), 2.28(2.04-2.55)], and primary and secondary school students without nutritional content in health education classes had higher rates of undernutrition [OR(95%CI)=1.12(1.03-1.23), 1.09(1.01-1.17)](all P < 0.05).

Conclusion

The prevalence of undernutrition is slightly higher in left-behind primary and secondary students than in non-left-behind primary and secondary students in central and western NIPRCES areas, with variations across different characteristics.

Nutrition policy  /  Nutritional status  /  Regression analysis  /  Students
Xin HU, Wenbin WANG, Wei CAO, Hongliang WANG, Mulei CHEN, Yao LIU, Titi YANG, Hui PAN, Ruihe LUO, Jianfen ZHANG, Qian ZHANG, Juan XU. Analysis of undernutrition and associated factors among left-behind and non-left-behind primary and secondary school students in the Nutrition Improvement Program areas in central and western China[J]. Chinese Journal of School Health, 2026 , 47 (3) : 327 -331 . DOI: 10.16835/j.cnki.1000-9817.2026094
Year 2026 volume 47 Issue 3
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doi: 10.16835/j.cnki.1000-9817.2026094
  • Receive Date:2025-11-25
  • Online Date:2026-05-08
  • Published:2026-03-25
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History
  • Received:2025-11-25
  • Revised:2026-01-11
Affiliations
    National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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