Brief communication (Original). Development and validation of a scale for “attitudes towards calcium consumption”

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Background: Attitude is recognized as a key determinant of health-related behaviors, including calcium intake for prevention of osteoporosis. Most existing instruments that measure attitudes towards calcium consumption are not appropriate for use in the Thai population because they focus on attitudes towards the consumption of dairy products, which are not a common source of calcium for Thais.

Objectives: To develop and validate an instrument for measuring attitudes towards calcium consumption among Thai adults.

Methods: An initial attitudinal scale (25 items) was developed and administered to 250 Thais (age ≥20 years) living in Khon Kaen, the largest province in the northeast Thailand, to assess its dimensions using exploratory factor analysis. Three factors were identified. The scale was reduced to 15 items and administered to 733 subjects to validate the identified factor structure and optimize the length of the scale.

Results: A three-factor model (10 items) was validated and interpreted as (1) a negative effect of calcium consumption on the body (4 items, reliability = 0.90), (2) the health benefits of calcium consumption for the body (3 items, reliability = 0.78), and (3) the need to take calcium on a regular basis (3 items, reliability = 0.86). The model fitted the data well (relative χ2 = 1.43, adjusted goodness-of-fit index = 0.98, confirmatory fit index = 0.997, root mean square error of approximation = 0.024).

Conclusion: The developed scale is a reliable and useful instrument for measuring attitudes towards calcium consumption. Further research is needed to validate the scale in different populations.

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  • 1. Rizzoli R Boonen S Brandi ML Burlet N Delmas P Reginster JY. The role of calcium and vitamin D in the management of osteoporosis. Bone.2008; 42:246-9.

  • 2. Rizzoli R Bianchi ML Garabedian M McKay HA Moreno LA. Maximizing bone mineral mass gain during growth for the prevention of fractures in the adolescents and the elderly. Bone. 2010; 46:294-305.

  • 3. Nordin BE. Calcium and osteoporosis. Nutrition. 1997; 13:664-86.

  • 4. Larson NI Story M Wall M Neumark-Sztainer D. Calcium and dairy intakes of adolescents are associated with their home environment taste preferences personal health beliefs and meal patterns. J Am Diet Assoc. 2006; 106:1816-24.

  • 5. Pon LW Noor-Aini MY Ong FB Frcog AN Mog SS Shamsuddin K et al. Diet nutritional knowledge and health status of urban middle-aged Malaysian women. Asia Pac J Clin Nutr. 2006; 15:388-99.

  • 6. Pongchaiyakul C Charoenkiatkul S Kosulwat V Rojroongwasinkul N Rajatanavin R. Dietary calcium intake among rural Thais in Northeastern Thailand. J Med Assoc Thai. 2008; 91:153-8.

  • 7. Korbangyang S. Health behavior related to osteoporosis of menopausal women in the rural area Nikomhuaipueng Subdistrict Hupueng District Kalasin province. Master’s thesis Khon Kaen University Thailand 2002.

  • 8. Phaitrakoon J. Relationship between dietary calcium intake exercise and bone mineral density in the first five postmenopausal years in Thai women Master’s thesis Mahidol University Thailand 2003.

  • 9. Thanuphon S. Study on foods habits and osteoporosis among menopausal women in Bangkok. Master’s thesis Kasetsart University Thailand 2003.

  • 10. Kanemasu Y. Thailand: a desk review of the school feeding programmes. World Food Programme. [online] 2007 [cited 2012 Dec 25]. Available from

  • 11. Knodel J Chayovan N. Population ageing and the well-being of older persons in Thailand. Population Studies Center Research Report 08-659 October 2008 University of Michigan. [online] 2008 [cited 2014 Jan 19]. Available from

  • 12. World Health Organization. Older population and health system: a profile of Thailand. [online] 2014 [cited 2014 Jan 19]. Available from

  • 13. Brewer JL Blake AJ Rankin SA Douglass LW. Theory of reasoned action predicts milk consumption in women. J Am Diet Assoc. 1999; 99:39-44.

  • 14. Glasman LR Albarracin D. Forming attitudes that predict future behavior: A meta-analysis of the attitudebehavior relation. Psychol Bull. 2006; 132:778-82.

  • 15. Susiyanti AE Chambers EIV. Calcium intake attitudes toward calcium-containing foods and number of risk factors for osteoporosis in two groups of 18 to 35 year-old women. Nutrition Research. 1996; 16:1313-29.

  • 16. Kim K Reicks M Sjoberg S. Applying the theory of planned behavior to predict dairy product consumption by older adults. J Nutr Educ Behav. 2003; 35:294-301.

  • 17. Cradler L. Are adolescent attitudes toward calciumrich foods and intake of dietary calcium related to the presence of grandparent (s) living in the household. Undergraduate thesis Purdue University United State of America. [online] 2012 [cited 2012 Dec 25]. Available from

  • 18. Himansu SM. Consumer behaviour- 4 : attitude. [online] 2012 [cited 2014 Jan 19]. Available from

  • 19. Ajzen I Fishbein M. The influence of attitudes on behavior. [online] 2013 [cited 2014 Jan 19]. Available from

  • 20. DeVellis RF. Scale development: theory and application 3rd ed. London: Sage Publications; 2012.

  • 21. Hogg MA Vaughan GM. Social psychology 5th ed. Essex: Pearson Education; 2008.

  • 22. Alwin DF. Feeling thermometers versus 7-point scales. Which are better? Sociol Meth Res. 1997; 25:310-40.

  • 23. Dawes J. Do data characteristics change according to the number of scale points used? An experiment using 5-point 7-point and 10-point scales. Int J Market Res. 2008; 50:61-77.

  • 24. Hulbert J. Information processing capacity and attitude measurement J Marketing Res. 1975; 12: 104-6.

  • 25. Rovinelli RJ Hambleton RK. On the use of content specialists in the assessment of criterion-referenced test item validity. Dutch J Educ Research.1977; 2: 49-60.

  • 26. Bryant FB Yarnold PR. Principal components analysis and exploratory and confirmatory factor analysis. In: Grimm LG Yarnold PR editors. Reading and understanding multivariate analysis. Washington DC: American Psychological Association 1995.

  • 27. Kline RB. Principles and practice of structural equation modeling 2nd ed. New York: Guilford Press; 2005.

  • 28. Pallant JF. SPSS survival manual. Maidenhead: Open University Press 2007.

  • 29. Pett M Lackey N Sullivan J. Making sense of factor analysis: The use of factor analysis for instrument development in health care research. California: Sage Publications; 2003.

  • 30. Comrey AL Lee HB. A first course in factor analysis. Hillsdale: Erlbaum; 1992.

  • 31. Nunnaly J. Psychometric theory. New York: McGraw- Hill; 1978.

  • 32. Holmes-Smith P Coote L Cunningham E. Structural equation modeling: from the fundamentals to advanced topics. Melbourne: School Research Evaluation and Measurement Services; 2006.

  • 33. Jaccard J Wan CK. LISREL Approaches to interaction effects in multiple regression. Thousand Oaks: Sage Publications; 1996.

  • 34. Fan X Thompson B Wang L. Effects of sample size estimation method and model specification on structural equation modeling fit indexes. Struct Equ Modeling. 1999; 6:56-83.

  • 35. Harrington D. Confirmatory factor analysis. New York: Oxford University Press; 2009.

  • 36. Garson D. Testing statistical assumptions. David Garson and Statistical Associates Publishing Blue book series. [online] 2012 [cited 2014 Jan 19]. Available from

  • 37. Fornell C Larcker D. Structural equation models with unobservable variables and measurement error. J Marketing Res. 1981; 3:39-50.

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