International Journal of Biometeorology

, Volume 58, Issue 5, pp 769–779 | Cite as

Predictive models and spatial variations of vital capacity in healthy people from 6 to 84 years old in China based on geographical factors

  • Jinwei He
  • Miao GeEmail author
  • Congxia WangEmail author
  • Naigui Jiang
  • Mingxin Zhang
  • Pujun Yun
Original Paper


The aim of this study was to provide a scientific basic for a unified standard of the reference value of vital capacity (VC) of healthy subjects from 6 and 84 years old in China. The normal reference value of VC was correlated to seven geographical factors, including altitude (X 1), annual duration of sunshine (X 2), annual mean air temperature (X 3), annual mean relative humidity (X 4), annual precipitation amount (X 5), annual air temperature range (X 6) and annual mean wind speed (X 7). Predictive models were established by five different linear and nonlinear methods. The best models were selected by t-test. The geographical distribution map of VC in different age groups can be interpolated by Kriging’s method using ArcGIS software. It was found that the correlation of VC and geographical factors in China was quite significant, especially for both males and females aged from 6 to 45. The best models were built for different age groups. The geographical distribution map shows the spatial variations of VC in China precisely. The VC of healthy subjects can be simulated by the best model or acquired from the geographical distribution map provided the geographical factors for that city or county of China are known.


Vital capacity Geographical factor Modeling Spatial variation 



The authors would like to thank all of the volunteers that took part in this study and the people for their assistance in technical and laboratory support. This study was supported by the National Natural Science Foundation of China (No. 40671005) and Innovation Funds of Graduate Programs (SNU, No. 2012CXB012).

Conflict of interest statement

None of the authors have any financial or other potential conflict of interest for this study.


  1. American Thoracic Society (1995) Standardization of spirometry (1994 update). Am J Respir Crit Care Med 152:1107–1136CrossRefGoogle Scholar
  2. Baltopoulos G, Fildisis G, Karatzas S, Georgiakodis F, Myrianthefs P (2000) Reference values and prediction equations for FVC and FEV1 in the greek elderly. Lung 178:201–212CrossRefGoogle Scholar
  3. Boskabady MH, Tashakory A, Mazloom R, Ghamami G (2004) Prediction equations for pulmonary function values in healthy young Iranians aged 8–18 years. Respirology 9(4):535–542CrossRefGoogle Scholar
  4. Chen GY, Wu XZ, Wang YC (2002) Discussion on the normal reference value of vital capacity. Second Med Educ 5:23Google Scholar
  5. Dang AR, Jia HF, Yi SZ (2003) Guide for Geographic information system application in ArcGIS 8 Desktop. Tsinghua University Press, Beijing, pp 79–301Google Scholar
  6. European Community for Coal and Steel (1983) Standardization of lung function tests. Bull Eur Physiopathol Respir 19(Suppl):1–93Google Scholar
  7. Facchini F, Fiori G, Bedogni G, Galletti L, Ismagulov O, Ismagulova A, Sharmanov T, Tsoy I, Belcastro MG, Rizzoli S, Goldoni M (2007) Spirometric reference values for children and adolescents from Kazakhstan. Ann Human Biol 34(5):519–534CrossRefGoogle Scholar
  8. Feng K, Chen L, Han SM, Zhu GJ (2011) Spirometric standards for healthy children and adolescents of Korean Chinese in Northeast China. J Kor Med Sci 26:1469–1473CrossRefGoogle Scholar
  9. Fiori G, Facchini F, Ismagulov O, Ismagulova A, Tarazona-Santos E, Pettener D (2000) Lung volume chest size and hematological variation in low- medium- and high-altitude central Asian populations. Am J Phys Anthropol 113:47–59CrossRefGoogle Scholar
  10. Garcia RF, Dorgham A, Pino JM, Villasante C, Garcia QC, Alvarez SR (2009) Lung volume reference values for women and men 65 to 85 years of age. Am J Respir Crit Care Med 180(11):1083–1091CrossRefGoogle Scholar
  11. Golshan M, Nematbakhsh M, Amra B, Crapo RO (2003) Spirometric reference values in a large Middle Eastern population. Eur Respir J 22:529–534CrossRefGoogle Scholar
  12. Gulshan S, James G (2006) Effect of aging on respiratory system physiology and immunology. Clin Interv Aging 1(3):253–260CrossRefGoogle Scholar
  13. Hankinson JL, Odencrantz JR, Fedan KB (1999) Spirometric reference values from a sample of the general U.S. population. Am J Respir Crit Care Med 159:179–187CrossRefGoogle Scholar
  14. He XL (2005) Research on multivariate linear model and ridge regression. Dissertation, Huazhong University of Science & Technology, pp 16–35Google Scholar
  15. Institue of Chinese Students’ Physique and Health Analysis (2002) Chinese students’ physique and health investigation and analysis in 2000. High Education, Beijing, pp 389–404Google Scholar
  16. Institue of Chinese Students’ Physique and Health Analysis (2007) Chinese students’ physique and health investigation and analysis in 2005. High Education, Beijing, pp 357–372Google Scholar
  17. Johns DP, Reid DW (2004) Influence of high altitude on lung development and function the lung: development aging and the environment. Academic, London, pp 267–275Google Scholar
  18. Kaditis AG, Gourgoulianis K, Tsoutsou P, Papaioannou AI, Fotiadou A, Messini C, Samaras K, Piperi M, Gissaki D, Zintzaras E, Molyvdas AP (2008) Spirometric values in Gypsy (Roma) children. Respir Med 102:1321–1328CrossRefGoogle Scholar
  19. Kuster SP, Kuster D, Schindler C, Rochat MK, Braun J, Held L, Brändli O (2008) Reference equations for lung function screening of healthy never-smoking adults aged 18–80 years. Eur Respir J 31:860–868CrossRefGoogle Scholar
  20. Lang JL, Fan YS (1993) Pulmonary function and cardiac function index of native populations in different altitude. Chin J Sports Med 44:113–114Google Scholar
  21. Li YY, Zhu ZX, Wang LC, Ning H (1995) Investigation on pulmonary function and arterlal blood gas analysis of healthy adults at high altitude. J Prev Med Chin People’s Liberation Army 60:265–268Google Scholar
  22. Liu J, Jiang WM, Yang KD (2001) The analyses of normal value of lung function in Mengzi area. Med Pharm Yunnan 22(6):476–477Google Scholar
  23. Milivojevic PL, Wells AU, Moody A, Fergusson W, Tukuitonga C, Kolbe J (2001) Spirometric lung volumes in the adult Pacific Islander population: comparison with predicted values in a European population. Respirology 6(3):247–253CrossRefGoogle Scholar
  24. Moore LG, Niermeye S, Zamudio S (1998) Human adaptation to high altitude: regional and life-cycle perspectives. Am J Phys Anthropol Suppl:25–64Google Scholar
  25. Mu KJ, Liu SW (1990) Nationwide normal values of lung function. PUMC & Beijing Medical University Publication, Beijing, pp 49–56Google Scholar
  26. Ostrowski S, Grzywa CA, Mieczkowska J, Rychlik M, Lachowska KP, Lopatyński J (2005) Pulmonary function between 40 and 80 years of age. J Physiol Pharmacol 56:127–133Google Scholar
  27. Pistelli F, Bottai M, Viegi G, Di PF, Carrozzi L, Baldacci S, Pedreschi M, Giuntini C (2000) Smooth reference equations for slow vital capacity and flow-volume curve indexes. Am J Respir Crit Care Med 161:899–905CrossRefGoogle Scholar
  28. Rawas OA, Baddar S, Maniri AA, Balaji J, Jayakrishnan B, Riyami BM (2009) Normal spirometric reference values for Omani adults. Lung 187:245–251CrossRefGoogle Scholar
  29. Ren ZH, Ma XM (2004) Lung capacity and physical indicators of students in the high altitude area. J Qinghai Univ (Science edition) 22(2):100–102Google Scholar
  30. Rogelio PP, Justino RP, Margarita R, Minerva C, Laura M, Rosalba R, Rocio C, Jaime V, Victor T, Victor BA, Gustavo O (2003) Spirometric function in children of Mexico City compared to Mexican-American children. Pediatr Pulmonol 35:177–183CrossRefGoogle Scholar
  31. Shen BH, Wang LD, Liang GP (2002) Testing and analyzing the lung capacity of youths and children. Hubei Sports Sci 21(1):16–18Google Scholar
  32. Smolej NN, Pavlović M, Zuskin E, Milicić J, Skarić JT, Barbalić M, Rudan P (2009) New reference equations for forced spirometry in elderly persons. Respir Med 103:621–628CrossRefGoogle Scholar
  33. Su MY, Gu HP, Yang Z (1992) Characteristics of lung function of highland immigrants in in-land after retirement. J High Altitude Med 5:47–49Google Scholar
  34. Tan WC, Bourbeau J, Hernandez P, Chapman K, Cowie R, FitzGerald MJ, Aaron S et al (2011) Canadian prediction equations of spirometric lung function for Caucasian adults 20 to 90 years of age: results from the Canadian Obstructive Lung Disease (COLD) study and the Lung Health Canadian Environment (LHCE) study. Can Respir J 18:321–326Google Scholar
  35. Tang GA, Yang X (2006) Geographic information system spatial analysis course based on ArcGIS. Science Press, Beijing, pp 50–203Google Scholar
  36. Trabelsi Y, Paries J, Harrabi I, Zbidi A, Tabka Z, Richalet JP, Buvry A (2008) Factors affecting the development of lung function in Tunisian children. Am J Hum Biol 20:716–725CrossRefGoogle Scholar
  37. Wang FB, Tang KX, Ding HL (2000a) A study on pulmonary volume in the 600 students. J Weifang Med Coll 22(3):186–187Google Scholar
  38. Wang T, Fan Y, Peng BZ, Wu F (2000b) Effect of lung function in plateau environment. Chin J Pest Control 79:381–383Google Scholar
  39. Wu Y, Zhang Z, Gang B, Love EJ (2009) Predictive equations for lung function based on a large occupational population in North China. J Occup Heal 51(6):471–477CrossRefGoogle Scholar
  40. Yan CN, Yan JH, Song JL (1991) The dictionary of cities and counties in China. Chinese Central Communist Party School Press, Beijing, pp 1–1446Google Scholar
  41. Yan H, Shen GQ, Mao YS (2002) Climatological atlas of the people’s republic of China. China Meteorological Press, Beijing, pp 1–250Google Scholar
  42. Zhang XZ, Fan YX (1990) Pulmonary ventilation function tests in Karakoram Mountain with different altitude. Chin J Appl Physiol 23:203Google Scholar
  43. Zhao J, Chen CK, Wu GH (2005) Geography of China. High Education Press, Beijing, pp 3–391Google Scholar
  44. Zheng JP, Zhong NS (2002) Normative values of pulmonary function testing in Chinese adults. Chin Med J 115(1):50–54Google Scholar
  45. Zheng JP, Chen RC, Zhong NS (2007) Pulmonary function. Guangdong Science and Technology, Guangzhou, pp 130–140Google Scholar
  46. Zhou KL, Kang YH (2005) Neural network model And simulation program design based on Matlab. Tsinghua University Press, Beijing, pp 86–135;140–157.Google Scholar
  47. Zhu GJ (2006) Physiological concentrations and psychological stage in Chinese Populatio- Population survey report in some provinces autonomous regions or city in China for the early 21st century. Peking Union Medical College Press, Beijing, pp 273–293Google Scholar

Copyright information

© ISB 2013

Authors and Affiliations

  1. 1.Institute of Healthy Geography, College of Tourism and EnvironmentShaanxi Normal UniversityXi’anChina
  2. 2.Second Affiliated Hospital of Medical CollegeXi’an Jiaotong UniversityXi’anChina

Personalised recommendations