Cardial-MASS-Study: Influencing Factors on Reliability of Selfreported Weight and Height

Cardiovascular Diseases Clinical Trial

Official title:

Cardial-MASS-Study: Influencing Factors on Reliability of Selfreported Weight and Height in Patients With Cardiovascular Disease

Clinical Trial Details — Status: Active, not recruiting

Administrative data

• NCT number: NCT04321057
• Other study ID #: Cardial-MASS
• Status: Active, not recruiting
• Start date: April 1, 2017
• Est. completion date: June 1, 2021

Study information

• Verified date: March 2020
• Source: Saarland University
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Height and weight are important informations in clinical life. Medication is dosed by them and weight, especially overweight, is a risk factor for cardiovascular diseases. Mostly you have to rely on the self-reported informations, because there is plenty of work and little time to weigh and measure every patient. But can the investigators really trust this informations? Former studies have shown, that most of self-reported heights and weights differ from the measured ones. This fact might lead to a wrong dosage of medicine or underestimated risk factors. So the Cardial-MASS-Study tries to detect influencing factors on the reliability of self-reported informations especially among patients, treated at the cardiological department at Saarland University.

Description:

Weight and height of patients is often recorded in clinical practice, as well as in clinical research. They give important informations for medication dosages, e.g., anticoagulants or anesthesias. Furthermore, the body mass index (BMI), calculated by weight and height, is an easy instrument to estimate a patient`s risk for cardiovascular diseases based on obesity.

In clinical practice, informations about height and weight do often rely on self-reported values instead of measured ones. This can be due to limited timely, but also instrumental resources, when scales or measuring tapes are not available. Unfortunately, these self-reported informations are often inaccurate. Age, education, weight, and sex seam to influence and distort them in different ways.

Former studies have shown, that a lot of patients overestimate their height [1-8] and underestimate their weight [1-6]. This might lead to a wrong classification in normal weight and overweight using BMI. Among elderly (>60 years) informations relying on measured values and on self-reported values seem to be even more divergent [10].

People with overweight are tending to underestimate their weight stronger than people with normal weight. The higher the weight, the more the self-reported information deviates from the actual weight [11,12]. Men`s informations are more exact than women`s, like Niedhammer et al. has shown in a study with 7350 participants [9]. Men with a BMI lower than 25 even overestimated their weight. Compared to younger ones, elderly men underestimated their weight more often, and elderly women`s self-reported weight was more accurate [1,9].

Next to age and gender, socioeconomic variables do influence self-reported measures. The higher the education or working position the more accurate the information about height. Noteworthy, women in high working positions overestimate their height, when compared to women in lower positions, who even underestimate their height [2,5,6,8,9].

Furthermore, external conditions of data acquisition may impact validity of self-reported information, too. Stewart supposed that informations given in an interview are more exact than those given in a questionnaire [11].

Most of the studies mentioned above are not exclusively related to patients with cardiovascular diseases. Studies referring to this patient population suggest, that men with cardiovascular diseases underestimate their weight less than others [13]. Nevertheless, Niedhammer et al. could not confirm this finding [9]. HEnce, the aim of this study is to identify factors that influence the validity of self-reported height and weight in patients with cardiovascular disease.

Recruitment information / eligibility

• Status: Active, not recruiting
• Enrollment: 731
• Est. completion date: June 1, 2021
• Est. primary completion date: July 1, 2020
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Patients at Innere Medizin III (Cardiology), Universitätsklinikum des Saarlandes (UKS)

• cardiovascular disease (Coronar-Vessel-Disease, Arrhythmia, Heart-attack, Hypertonus, stable heart failure)

• Patients at a family doctor

Exclusion Criteria:

• younger than 18 years

• Dementia

• cardial decompensation

• severe anemia (Hemoglobin<9 mg/dl)

• cardial shock

• acute kidney failure

• factors, that prevent patients from answering the questionnaire

• factors, that prevent patients from being measured and weighted

Related Conditions & MeSH terms

• Cardiovascular Diseases

Locations

Country	Name	City	State
Germany	Clinic for Internal Medicine, Cardioloy, Angioloy, and Internal Intensive Care Medicine, Saarland University Hospital	Homburg	Saarland

Sponsors (1)

Lead Sponsor	Collaborator
Saarland University

Country where clinical trial is conducted

Germany, 

References & Publications (22)

Bender R, Trautner C, Spraul M, Berger M. Assessment of excess mortality in obesity. Am J Epidemiol. 1998 Jan 1;147(1):42-8. — View Citation

Boström G, Diderichsen F. Socioeconomic differentials in misclassification of height, weight and body mass index based on questionnaire data. Int J Epidemiol. 1997 Aug;26(4):860-6. — View Citation

Bowlin SJ, Morrill BD, Nafziger AN, Jenkins PL, Lewis C, Pearson TA. Validity of cardiovascular disease risk factors assessed by telephone survey: the Behavioral Risk Factor Survey. J Clin Epidemiol. 1993 Jun;46(6):561-71. — View Citation

Bray GA. Overweight is risking fate. Definition, classification, prevalence, and risks. Ann N Y Acad Sci. 1987;499:14-28. Review. — View Citation

Coe TR, Halkes M, Houghton K, Jefferson D. The accuracy of visual estimation of weight and height in pre-operative supine patients. Anaesthesia. 1999 Jun;54(6):582-6. — View Citation

Dorn JM, Schisterman EF, Winkelstein W Jr, Trevisan M. Body mass index and mortality in a general population sample of men and women. The Buffalo Health Study. Am J Epidemiol. 1997 Dec 1;146(11):919-31. — View Citation

Foil MB, Collier MS, MacDonald KG Jr, Pories WJ. Availability and Adequacy of Diagnostic and Therapeutic Equipment for the Morbidly Obese Patient in an Acute Care Setting. Obes Surg. 1993 May;3(2):153-156. — View Citation

Hendershot KM, Robinson L, Roland J, Vaziri K, Rizzo AG, Fakhry SM. Estimated height, weight, and body mass index: implications for research and patient safety. J Am Coll Surg. 2006 Dec;203(6):887-93. Epub 2006 Oct 25. — View Citation

Jalkanen L, Tuomilehto J, Tanskanen A, Puska P. Accuracy of self-reported body weight compared to measured body weight. A population survey. Scand J Soc Med. 1987;15(3):191-8. — View Citation

Jeffery RW. Bias in reported body weight as a function of education, occupation, health and weight concern. Addict Behav. 1996 Mar-Apr;21(2):217-22. — View Citation

Kuczmarski MF, Kuczmarski RJ, Najjar M. Effects of age on validity of self-reported height, weight, and body mass index: findings from the Third National Health and Nutrition Examination Survey, 1988-1994. J Am Diet Assoc. 2001 Jan;101(1):28-34; quiz 35-6. — View Citation

Kurth T, Gaziano JM, Berger K, Kase CS, Rexrode KM, Cook NR, Buring JE, Manson JE. Body mass index and the risk of stroke in men. Arch Intern Med. 2002 Dec 9-23;162(22):2557-62. — View Citation

Lavie CJ, Milani RV, Ventura HO. Obesity and cardiovascular disease: risk factor, paradox, and impact of weight loss. J Am Coll Cardiol. 2009 May 26;53(21):1925-32. doi: 10.1016/j.jacc.2008.12.068. Review. — View Citation

Millar WJ. Distribution of body weight and height: comparison of estimates based on self-reported and observed measures. J Epidemiol Community Health. 1986 Dec;40(4):319-23. — View Citation

Niedhammer I, Bugel I, Bonenfant S, Goldberg M, Leclerc A. Validity of self-reported weight and height in the French GAZEL cohort. Int J Obes Relat Metab Disord. 2000 Sep;24(9):1111-8. — View Citation

Palta M, Prineas RJ, Berman R, Hannan P. Comparison of self-reported and measured height and weight. Am J Epidemiol. 1982 Feb;115(2):223-30. — View Citation

Pi-Sunyer FX. Medical hazards of obesity. Ann Intern Med. 1993 Oct 1;119(7 Pt 2):655-60. Review. — View Citation

Roberts RJ. Can self-reported data accurately describe the prevalence of overweight? Public Health. 1995 Jul;109(4):275-84. — View Citation

Rowland ML. Self-reported weight and height. Am J Clin Nutr. 1990 Dec;52(6):1125-33. — View Citation

Stewart AL. The reliability and validity of self-reported weight and height. J Chronic Dis. 1982;35(4):295-309. — View Citation

Stewart AW, Jackson RT, Ford MA, Beaglehole R. Underestimation of relative weight by use of self-reported height and weight. Am J Epidemiol. 1987 Jan;125(1):122-6. — View Citation

Ziebland S, Thorogood M, Fuller A, Muir J. Desire for the body normal: body image and discrepancies between self reported and measured height and weight in a British population. J Epidemiol Community Health. 1996 Feb;50(1):105-6. — View Citation

* Note: There are 22 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Self-reported weight	Patient´s self-reported weight and the measured weight will be compared.	baseline
Primary	Self-reported height	Patient´s self-reported height and the measured height will be compared.	baseline