Journal of Preventive Medicine and Public Health

  • 제46권6호
  • /
  • Pages.336-345
  • /
  • 2013
  • /
  • 1975-8375(pISSN)
  • /
  • 2233-4521(eISSN)
대한예방의학회 (The Korean Society for Preventive Medicine)
권호 표지
DOI QR코드

DOI QR Code

Social Network Characteristics and Body Mass Index in an Elderly Korean Population

  • Lee, Won Joon (Department of Preventive Medicine, Yonsei University College of Medicine) ;
  • Youm, Yoosik (Department of Sociology, Yonsei University College of Social Sciences) ;
  • Rhee, Yumie (Department of Internal Medicine, Yonsei University College of Medicine) ;
  • Park, Yeong-Ran (Division of Silver Industry, Kangnam University) ;
  • Chu, Sang Hui (Department of Clinical Nursing Science, Yonsei University College of Nursing) ;
  • Kim, Hyeon Chang (Department of Preventive Medicine, Yonsei University College of Medicine)
  • 투고 : 2013.05.24
  • 심사 : 2013.10.17
  • 발행 : 2013.11.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

Objectives: Research has shown that obesity appears to spread through social ties. However, the association between other characteristics of social networks and obesity is unclear. This study aimed to identify the association between social network characteristics and body mass index (BMI, $kg/m^2$) in an elderly Korean population. Methods: This cross-sectional study analyzed data from 657 Koreans (273 men, 384 women) aged 60 years or older who participated in the Korean Social Life, Health, and Aging Project. Network size is a count of the number of friends. Density of communication network is the number of connections in the social network reported as a fraction of the total links possible in the personal (ego-centric) network. Average frequency of communication (or meeting) measures how often network members communicate (or meet) each other. The association of each social network measure with BMI was investigated by multiple linear regression analysis. Results: After adjusting for potential confounders, the men with lower density (<0.71) and higher network size (4-6) had the higher BMI (${\beta}$=1.089, p=0.037) compared to the men with higher density (>0.83) and lower size (1-2), but not in the women (p=0.393). The lowest tertile of communication frequency was associated with higher BMI in the women (${\beta}$=0.885, p=0.049), but not in the men (p=0.140). Conclusions: Our study suggests that social network structure (network size and density) and activation (communication frequency and meeting frequency) are associated with obesity among the elderly. There may also be gender differences in this association.

키워드

참고문헌

  1. Cassel J. The contribution of the social environment to host resistance: the Fourth Wade Hampton Frost Lecture. Am J Epidemiol 1976;104(2):107-123. https://doi.org/10.1093/oxfordjournals.aje.a112281
  2. Cobb S. Presidential Address-1976. Social support as a moderator of life stress. Psychosom Med 1976;38(5):300-314.
  3. Berkman LF, Syme SL. Social networks, host resistance, and mortality: a nine-year follow-up study of Alameda County residents. Am J Epidemiol 1979;109(2):186-204.
  4. Blazer DG. Social support and mortality in an elderly community population. Am J Epidemiol 1982;115(5):684-694. https://doi.org/10.1093/oxfordjournals.aje.a113351
  5. House JS, Robbins C, Metzner HL. The association of social relationships and activities with mortality: prospective evidence from the Tecumseh Community Health Study. Am J Epidemiol 1982;116(1):123-140. https://doi.org/10.1093/oxfordjournals.aje.a113387
  6. Haslam DW, James WP. Obesity. Lancet 2005;366(9492):1197-1209. https://doi.org/10.1016/S0140-6736(05)67483-1
  7. Helleringer S, Kohler HP. Sexual network structure and the spread of HIV in Africa: evidence from Likoma Island, Malawi. AIDS 2007;21(17):2323-2332. https://doi.org/10.1097/QAD.0b013e328285df98
  8. Laumann EO, Youm Y. Racial/ethnic group differences in the prevalence of sexually transmitted diseases in the United States: a network explanation. Sex Transm Dis 1999;26(5):250-261. https://doi.org/10.1097/00007435-199905000-00003
  9. Liljeros F, Edling CR, Amaral LA, Stanley HE, Aberg Y. The web of human sexual contacts. Nature 2001;411(6840):907-908. https://doi.org/10.1038/35082140
  10. Klovdahl AS, Graviss EA, Yaganehdoost A, Ross MW, Wanger A, Adams GJ, et al. Networks and tuberculosis: an undetected community outbreak involving public places. Soc Sci Med 2001;52(5):681-694. https://doi.org/10.1016/S0277-9536(00)00170-2
  11. Mettikolla P, Calander N, Luchowski R, Gryczynski I, Gryczynski Z, Zhao J, et al. Cross-bridge kinetics in myofibrils containing familial hypertrophic cardiomyopathy R58Q mutation in the regulatory light chain of myosin. J Theor Biol 2011;284(1):71-81. https://doi.org/10.1016/j.jtbi.2011.06.014
  12. Ancel Meyers L, Newman ME, Martin M, Schrag S. Applying network theory to epidemics: control measures for Mycoplasma pneumoniae outbreaks. Emerg Infect Dis 2003;9:204-210. https://doi.org/10.3201/eid0902.020188
  13. Rosenquist JN, Fowler JH, Christakis NA. Social network determinants of depression. Mol Psychiatry 2011;16(3):273-281. https://doi.org/10.1038/mp.2010.13
  14. Bearman PS, Moody J. Suicide and friendships among American adolescents. Am J Public Health 2004;94(1):89-95. https://doi.org/10.2105/AJPH.94.1.89
  15. Fowler JH, Christakis NA. Dynamic spread of happiness in a large social network: longitudinal analysis over 20 years in the Framingham Heart Study. BMJ 2008;337:a2338. https://doi.org/10.1136/bmj.a2338
  16. Berkman LF, Kawachi I. Social epidemiology. New York: Oxford University Press; 2000, p. 145-149.
  17. Van Gaal LF, Mertens IL, De Block CE. Mechanisms linking obesity with cardiovascular disease. Nature 2006;444(7121): 875-880. https://doi.org/10.1038/nature05487
  18. Christakis NA, Fowler JH. The spread of obesity in a large social network over 32 years. N Engl J Med 2007;357(4):370-379. https://doi.org/10.1056/NEJMsa066082
  19. Fowler JH, Christakis NA. Estimating peer effects on health in social networks: a response to Cohen-Cole and Fletcher; and Trogdon, Nonnemaker, and Pais. J Health Econ 2008;27(5): 1400-1405. https://doi.org/10.1016/j.jhealeco.2008.07.001
  20. Halliday TJ, Kwak S. Weight gain in adolescents and their peers. Econ Hum Biol 2009;7(2):181-190. https://doi.org/10.1016/j.ehb.2009.05.002
  21. Renna F, Grafova IB, Thakur N. The effect of friends on adolescent body weight. Econ Hum Biol 2008;6(3):377-387. https://doi.org/10.1016/j.ehb.2008.06.005
  22. Trogdon JG, Nonnemaker J, Pais J. Peer effects in adolescent overweight. J Health Econ 2008;27(5):1388-1399. https://doi.org/10.1016/j.jhealeco.2008.05.003
  23. Valente TW, Fujimoto K, Chou CP, Spruijt-Metz D. Adolescent affiliations and adiposity: a social network analysis of friendships and obesity. J Adolesc Health 2009;45(2):202-204. https://doi.org/10.1016/j.jadohealth.2009.01.007
  24. Cornwell B, Schumm LP, Laumann EO, Graber J. Social Networks in the NSHAP Study: rationale, measurement, and preliminary findings. J Gerontol B Psychol Sci Soc Sci 2009;64 Suppl 1:i47-i55.
  25. Valente TW. Social networks and health: models, methods, and applications. New York: Oxford University Press; 2010, p. 44-45, 69-70.
  26. Uchino BN. Social support and health: a review of physiological processes potentially underlying links to disease outcomes. J Behav Med 2006;29(4):377-387. https://doi.org/10.1007/s10865-006-9056-5
  27. Bahr DB, Browning RC, Wyatt HR, Hill JO. Exploiting social networks to mitigate the obesity epidemic. Obesity (Silver Spring) 2009;17(4):723-728. https://doi.org/10.1038/oby.2008.615
  28. Schlundt DG, Hill JO, Sbrocco T, Pope-Cordle J, Kasser T. Obesity: a biogenetic or biobehavioral problem. Int J Obes 1990; 14(9):815-828.
  29. Kohl HW 3rd, Hobbs KE. Development of physical activity behaviors among children and adolescents. Pediatrics 1998; 101(3 Pt 2):549-554.
  30. Haines J, Neumark-Sztainer D. Prevention of obesity and eating disorders: a consideration of shared risk factors. Health Educ Res 2006;21(6):770-782. https://doi.org/10.1093/her/cyl094
  31. Cullen KW, Klesges LM, Sherwood NE, Baranowski T, Beech B, Pratt C, et al. Measurement characteristics of diet-related psychosocial questionnaires among African-American parents and their 8- to 10-year-old daughters: results from the Girls' health Enrichment Multi-site Studies. Prev Med 2004;38 Suppl: S34-S42. https://doi.org/10.1016/j.ypmed.2003.05.002
  32. Eisenberg ME, Neumark-Sztainer D, Story M, Perry C. The role of social norms and friends' influences on unhealthy weight-control behaviors among adolescent girls. Soc Sci Med 2005; 60(6):1165-1173. https://doi.org/10.1016/j.socscimed.2004.06.055
  33. Kadushin C. Understanding social networks: theories, concepts, and findings. New York: Oxford University Press; 2012, p. 29-30.
  34. Ross CE, Wu CL. The links between education and health. Am Sociol Rev 1995;60(5):719-745. https://doi.org/10.2307/2096319
  35. Oliveira AJ, Rostila M, de Leon AP, Lopes CS. The influence of social relationships on obesity: sex differences in a longitudinal study. Obesity (Silver Spring) 2013;21(8):1540-1547. https://doi.org/10.1002/oby.20286
  36. Szklo M, Nieto FJ. Epidemiology: beyond the basics. Sudbury: Jones and Bartlett Publishers; 2007, p. 211-212.
  37. Zheng W, McLerran DF, Rolland B, Zhang X, Inoue M, Matsuo K, et al. Association between body-mass index and risk of death in more than 1 million Asians. N Engl J Med 2011;364(8):719-729. https://doi.org/10.1056/NEJMoa1010679
  38. Jee SH, Sull JW, Park J, Lee SY, Ohrr H, Guallar E, et al. Body-mass index and mortality in Korean men and women. N Engl J Med 2006;355(8):779-787. https://doi.org/10.1056/NEJMoa054017
  39. Manson JE, Bassuk SS, Hu FB, Stampfer MJ, Colditz GA, Willett WC. Estimating the number of deaths due to obesity: can the divergent findings be reconciled? J Womens Health (Larchmt) 2007;16(2):168-176. https://doi.org/10.1089/jwh.2006.0080
  40. Lopez-Jimenez F. Speakable and unspeakable facts about BMI and mortality. Lancet 2009;373(9669):1055-1056. https://doi.org/10.1016/S0140-6736(09)60628-0

피인용 문헌

  1. The Korean Social Life, Health and Aging Project-Health Examination Cohort vol.36, pp.None, 2014, https://doi.org/10.4178/epih/e2014003
  2. Obesity in older persons : vol.18, pp.1, 2013, https://doi.org/10.1097/mco.0000000000000113
  3. O Programa Nacional de Controle do Tabagismo (PNCT) na perspectiva social: a análise de redes, capital e apoio social vol.23, pp.4, 2013, https://doi.org/10.1590/1414-462x201500040241
  4. Factors Associated with Insomnia among the Elderly in a Korean Rural Community vol.14, pp.4, 2013, https://doi.org/10.4306/pi.2017.14.4.400
  5. The Connection Prescription: Using the Power of Social Interactions and the Deep Desire for Connectedness to Empower Health and Wellness vol.11, pp.6, 2013, https://doi.org/10.1177/1559827615608788
  6. Is the Relationship between Depression and C Reactive Protein Level Moderated by Social Support in Elderly?-Korean Social Life, Health, and Aging Project (KSHAP) vol.15, pp.1, 2013, https://doi.org/10.4306/pi.2018.15.1.24
  7. Social Network Analysis and Resilience in University Students: An Approach from Cohesiveness vol.15, pp.10, 2013, https://doi.org/10.3390/ijerph15102119
  8. The association between obesity and social exclusion in middle-aged and older adults: findings from a nationally representative study in Germany vol.18, pp.None, 2013, https://doi.org/10.1186/s12877-018-0946-5
  9. Personal network characteristics and body mass index: the role of education among Black Americans vol.41, pp.1, 2019, https://doi.org/10.1093/pubmed/fdy020
  10. Social support, social network and salt-reduction behaviours in children: a substudy of the School-EduSalt trial vol.9, pp.6, 2019, https://doi.org/10.1136/bmjopen-2018-028126
  11. 건강의 사회적 결정요인과 필요 치과진료 미수진과의 관련성 vol.20, pp.2, 2013, https://doi.org/10.5392/jkca.2020.20.02.360
  12. Associations between social connections, their interactions, and obesity differ by gender: A population-based, cross-sectional analysis of the Canadian Longitudinal Study on Aging vol.15, pp.7, 2013, https://doi.org/10.1371/journal.pone.0235977
  13. Adiposity and the role of diverse social supports: an observational, gender-sensitive study using the baseline Canadian Longitudinal Study on Aging vol.24, pp.18, 2013, https://doi.org/10.1017/s1368980021003724