Over the past 50 years, cancer research has emphasized individual behaviors (e.g., early detection screening, smoking, alcohol use, diet and nutrition, and physical activity) as important foci for prevention (Hataway & Bragg, 1984 xClose
Hataway, J., & Bragg, C. (1984). Cancer: What is prevention? Family & Community Health, 7(1), 59-71.). Self-report instruments are among the primary methods of assessing cancer-related variables, including early detection screening and behavioral risk factors (primary prevention), as well as psychosocial risk factors (secondary and tertiary prevention). This section discusses self-reported cancer screening and considerations for the use of self-reported behavior and psychosocial risk factors, and concludes with suggestions about how to most effectively use and interpret self-report data.
Self-reported cancer screening. Cancer screening is a commonly reported clinical assessment designed to facilitate early detection, and regular screening is important for reducing morbidity and mortality across an array of cancer types. Although more objective alternatives exist for determining screening practices in the population (e.g., health insurance or medical records), self-report of screening is nonetheless the measure of choice in the majority of studies. For example, about two-thirds of research examining Pap smear testing utilized self-report methods (Newell, Girgis, Sanson-Fisher, Savolainen, & Hons, 1999 xClose
Newell, S.A., Girgis, A., Sanson-Fisher, R., & Savolainen, N.J. (1999). The accuracy of self-reported health behaviors and risk factors relating to cancer and cardiovascular disease in the general population: A critical review. American Journal of Preventive Medicine, 17(3), 211-229.).
With the growing emphasis on preventive care, a body of research has tested strategies aimed at encouraging patients to be screened in accordance with recommended guidelines (e.g., Masi, Blackman, & Peek, 2007 xClose
Masi, C.M., Blackman, D.J., & Peek, M.E. (2007). Interventions to enhance breast cancer screening, diagnosis, and treatment among racial and ethnic minority women. Medical Care Research and Review, 64, 195S-242S.). Although increased screening is not universally recommended, efforts to promote screening are common – including, but not limited to, screening for breast, cervical, ovarian, colorectal, and prostate cancers. Self-report validity studies often report kappa (i.e., percent agreement), sensitivity (i.e., true positives—the proportion of participants screened according to objective markers who self-reported the screening), and specificity (i.e., true negatives—the proportion of participants not screened according to objective markers who self-reported no-screening). Concordance rates for medical records and self-reported data indicate that the prevalence of cancer screening is overestimated by self-report (Gordon, Hiatt, & Lampert, 1993 xClose
Gordon, N.P., Hiatt, R.A., & Lampert, D.I. (1993). Concordance of self-reported data and medical record audit for six cancer screening procedures. Journal of the National Cancer Institute, 85(7), 566-570.; Hiatt et al., 1995 xClose
Hiatt, R.A., Perez-Stable, E.J., Quesenberry, Jr., C., Sabogal, F., Otero-Sabogal, R., & McPhee, S.J. (1995). Agreement between self-reported early cancer detection practices and medical audits among Hispanic and non-Hispanic white health plan members in North Carolina. Preventive Medicine, 24, 278-285.), whereas the time since the most recent test is underestimated (Gordon et al., 1993 xClose
Gordon, N.P., Hiatt, R.A., & Lampert, D.I. (1993). Concordance of self-reported data and medical record audit for six cancer screening procedures. Journal of the National Cancer Institute, 85(7), 566-570.). Research in other areas has found that people can often accurately report the day of week a given event occurred, yet they tend to report a more recent date than actually was the case (Cohen & Java, 1995 xClose
Cohen, G., & Java, R. (1995). Memory for medical history: Accuracy of recall. Applied Cognitive Psychology, 9, 273-288.; Thompson, Skowronski, & Lee, 1988 xClose
Thompson, C.P., Skowronski, J.J., & Lee, D.J. (1988). Telescoping in dating naturally occurring events. Memory and Cognition, 16, 461-468.). This may occur because greater clarity of a memory provokes feelings of recency (Bradburn et al., 1987 xClose
Bradburn, N.M., Rips, L.J., & Shevell, S.K. (1987). Answering autobiographical questions: The impact of memory and inference on surveys. Science, 236, 157-161.). Along these lines, people tend to anchor their reports to reasonable timeframes and/or round the values off to the number of weeks or months (Huttenlocher et al., 1990 xClose
Huttenlocher, J., Hedges, L.V., & Bradburn, N.M. (1990). Reports of elapsed time: Bounding and rounding processes in estimation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 16(2), 196-213.). Each of these lines of evidence suggests that report of specific dates or the duration of time passed since an event may be inaccurate. The sources of these biases are unclear, but they likely reflect individuals’ reliance on schemas when answering temporally-based questions.
Although findings are mixed, the utility of self-report data for some specific types of screening is promising. Some research has found high sensitivity and agreement for breast and cervical cancer screening (Caplan et al., 2003 xClose
Caplan, L.S., McQueen, D.V., Qualters, J.R., Leff, M., Garrett, C., Calonge, N. (2003). Validity of women’s self-report of cancer screening test utilization in a managed care population. Cancer Epidemiology, Biomarkers, and Prevention, 12, 1182-1187.), although other research has not (Bowman, Redman, Dickinson, Gibberd, & Sanson-Fisher, 1991 xClose
Bowman, J.A., Redman, S., Dickinson, J.A., Gibberd, R., & Sanson-Fisher, R.W. (1991). The accuracy of Pap smear utilization self-report: A methodological consideration in cervical screening research. Health Services Research, 26(1), 97-107.; Bowman, Sanson-Fisher, & Redman, 1997 xClose
Bowman, J.A., Sanson-Fisher, R., & Redman, S. (1997). The accuracy of self-reported Pap smear utilization. Social Science and Medicine, 44(7), 969-976.). Lykins, Pavlik, and Andrykowski (2007) xClose
Lykins, E.L., Pavlik, E.L., & Andrykowski, M.A. (2007). Validity of self-reports of return for routine repeat screening in an ovarian cancer screening program. Cancer Epidemiology, Biomarkers, and Prevention, 16(3), 490-493. concluded that the validity of self-report for determining routine ovarian cancer screening (i.e., transvaginal sonography; TVS) was very high when compared to medical records. Indeed, their evidence suggests that TVS self-reports are more accurate than breast, cervical, and colorectal cancer screening reports. Despite these encouraging findings, however, accuracy of self-reported mammography and Pap smear testing for clinical decision-making may be lower among low socioeconomic, underinsured, and/or minority groups (McGovern, Lurie, Margolis, & Slater, 1998 xClose
McGovern, P.G., Lurie, N., Margolis, K.L., & Slater, J.S. (1998). Accuracy of self-report of mammography and Pap smear in a low-income urban population. American Journal of Preventive Medicine, 14(3), 201-208.; McPhee et al., 2002 xClose
McPhee, S.J., Nguyen, T.T., Shema, S.J., Nguyen, B., Somkin, C., Vo, P., et al. (2002). Validation of recall of breast and cervical cancer screening by women in an ethnically diverse population. Preventive Medicine, 35, 463-473.; Vacek, Mickey, & Worden, 1997 xClose
Vacek, P.M., Mickey, R.M., & Worden, J.K. (1997). Reliability of self-reported breast screening information in a survey of lower income women. Preventive Medicine, 26, 287-291.). Fewer studies have examined the use of self-report for colorectal or prostate cancer screening, but existing evidence suggests high (Bleiker et al., 2005 xClose
Bleiker, E.M., Menko, F.H., Taal, B.G., Kluijt, I., Wever, L.D., Gerritsma, M.A., et al. (2005). Screening behavior of individuals at high risk for colorectal cancer. Gastroenterology, 128(2), 280-287.), or fair to moderate concordance with medical records (Hall et al., 2004 xClose
Hall, H.I., Van Den Eeden, S.K., Tolsma, D.D., Rardin, K., Thompson, T., Sinclair, A.H., et al. (2004). Testing for prostate and colorectal cancer: comparison of self-report and medical record audit. Preventive Medicine, 39, 27-35.; Jordan, Price, King, Masyk, & Bedell, 1999 xClose
Jordan, T.R., Price, J.H., King, K.A., Masyk, T., Bedell, A.W. (1999). The validity of male patients’ self-reports regarding prostate cancer screening. Preventive Medicine, 28, 297-303.).
Overall, research suggests that patient self-reports of cancer screening are reasonably valid. However, the precision of estimates of timing are considerably less reliable (e.g., specific dates or the time since the most recent screening). It is important to note, however, that patient reports are not always intentionally biased. For example, several types of screening can be conducted as part of a full examination, leaving patients unaware that a particular test was conducted (Hall et al., 2004 xClose
Hall, H.I., Van Den Eeden, S.K., Tolsma, D.D., Rardin, K., Thompson, T., Sinclair, A.H., et al. (2004). Testing for prostate and colorectal cancer: comparison of self-report and medical record audit. Preventive Medicine, 39, 27-35.).
Self-reports of cancer risk behaviors. Cancer risk is elevated by the presence of both uncontrollable and controllable risk factors. Self-reports are used to estimate the prevalence of risk factors in the population and the efficacy of interventions seeking to reduce them. Risk factors that are beyond one’s control generally include family history/genetics, race/ethnicity, prior history of cancer, and age. However, there are a number of controllable risk factors that are related to behavior, such as smoking, heavy alcohol use, poor diet/nutrition, physical inactivity, ultraviolet light exposure, and risky sexual behavior. A complete review of the nature of self-reports of these factors is beyond the scope of this discussion; rather, our aim is to consider several key variables related to cancer risk, and to briefly describe evidence for the validity of their self-report. Newell and colleagues (1999) xClose
Newell, S.A., Girgis, A., Sanson-Fisher, R., & Savolainen, N.J. (1999). The accuracy of self-reported health behaviors and risk factors relating to cancer and cardiovascular disease in the general population: A critical review. American Journal of Preventive Medicine, 17(3), 211-229. conducted a comprehensive review of the accuracy of self-reported health behaviors and cancer-related risk factors. They found that, in general, self-reports consistently underestimated risk factor prevalence and percentages of ‘at-risk’ individuals.
Tobacco smoking is the leading cause of preventable cancer morbidity and mortality, making smoking status into one of the most commonly reported cancer-related risk factors. Earlier research revealed a tendency for smokers to underreport (e.g., Haley & Hoffman, 1985 xClose
Haley, N., & Hoffman, D. (1985). Analysis for nicotine and cotinine in hair to determine cigarette smoking status. Clinical Chemistry, 31, 1598-1600.) or deny their smoking completely (e.g., Luepker, Pallonen, Murray, & Pirie, 1989 xClose
Luepker, R., Pallonen, U., Murray, D., & Pirie, P. (1989). Validity of telephone surveys in assessing cigarette smoking in young adults. American Journal of Public Health, 79, 202-204.; Murray, O’Connell, Schmidy, & Perry, 1987 xClose
Murray, D., O’Connell, C., Schmid, L., & Perry, C. (1987). The validity of smoking self-reports by adolescents: A re-examination of the bogus pipeline procedure. Addictive Behaviors, 12, 7-15.). More recently, however, evidence suggests that smokers are willing to self-disclose this behavior. Patrick and colleagues (1994) xClose
Patrick, D., Cheadle, A., Thompson, D. C., Diehr, P., Koepsell, T., & Kinne, S. (1994). The validity of self-reported smoking: A review and meta-analysis. American Journal of Public Health, 84, 1086-1093. found that the overall validity of smoking self-reports is high, with sensitivity and specificity estimates of close to 90%. Self-reports of cigarette smoking also appear to be valid among adolescents across racial/ethnic groups (Kentala, Utriainen, Pahkala, & Mattila, 2004 xClose
Kentala, J., Utriainen, P., Pahkala, K., & Mattila, K. (2004). Verification of adolescent self-reported smoking. Addictive Behaviors, 29, 405-411.; Wills & Cleary, 1997 xClose
Wills, T.A., & Cleary, S.D. (1997). The validity of self-reports of smoking: Analyses by race/ethnicity in a school sample of urban adolescents. American Journal of Public Health, 87(1), 56-61.). Some recent work, however, suggests that the accuracy of self-reports may be declining, perhaps in conjunction with the underreporting of illicit drug use (Fendrich, Mackesy-Amiti, Johnson, Hubbell, & Wislar, 2005 xClose
Fendrich, M., Mackesy-Amiti, M.E., Johnson, T.P., Hubbell, A., & Wislar, J.S. (2005). Tobacco-reporting validity in an epidemiological drug-use survey. Addictive Behaviors, 30, 175-181.).
Clinical trials using self-reported smoking abstinence as an outcome should follow recommended definitions (c.f. Hughes et al., 2003 xClose
Hughes, J.R., Keely, J.P., Niaura, R.S., Ossip-Klein, D.J., Richmond, R.L., & Swan, G.E. (2003). Measures of abstinence in clinical trials: Issues and recommendations. Nicotine and Tobacco Research, 5, 13-25.). Whenever possible, researchers should biochemically validate smoking status using gold standard markers, such as carbon monoxide (CO), salivary cotinine, or thiocyanate. Researchers should also consider the possible role of social desirability in smoking status reports. In particular, certain types of smokers may have a higher likelihood of underreporting, including those with chronic diseases (Fisher, Taylor, Shelton, & Debanne, 2007 xClose
Fisher, M.A., Taylor, G.W., Shelton, B.J., & Debanne, S.M. (2007). Sociodemographic characteristics and diabetes predict invalid self-reported non-smoking in a population-based study of U.S. adults. BioMed Central Public Health, 7, 33.), pregnant women (Russell, Crawford, & Woodby, 2004 xClose
Russell, T., Crawford, M., & Woodby, L. (2004). Measurements for active cigarette smoke exposure in prevalence and cessation studies: Why simply asking pregnant women isn’t enough. Nicotine and Tobacco Research, 6(2), S141-151.), and hospital inpatients (Schofield & Hill, 1999 xClose
Schofield, P.E., & Hill, D.J. (1999). How accurate is in-patient smoking status data collected by hospital admissions staff. Aust NZ J Public Health, 23, 654-656.).
Heavy alcohol use is associated with elevated cancer risk (Cargiulo, 2007 xClose
Cargiulo, T. (2007). Understanding the health impact of alcohol dependence. American Journal of Health-System Pharmacy, 64(5), S5-S11.). The gold standard for biochemical verification of short-term alcohol use is a breathalyzer test; yet this test is infrequently used in research (see Newell et al., 1999 xClose
Newell, S.A., Girgis, A., Sanson-Fisher, R., & Savolainen, N.J. (1999). The accuracy of self-reported health behaviors and risk factors relating to cancer and cardiovascular disease in the general population: A critical review. American Journal of Preventive Medicine, 17(3), 211-229.). Grønbaek and Heitmann (1996) xClose
Grønbaek, M., & Heitmann, B.L. (1996). Validity of self-reported intakes of wine, beer, and spirits in population studies. European Journal of Clinical Nutrition, 50(7), 487-490. found overall agreement between self-reports on an alcohol use frequency questionnaire and dietary interviews. However, the number of studies that carefully examine the validity of self-report of alcohol use is not yet adequate to form firm conclusions. Even in the absence of biochemical verification, the "bogus pipeline" (a procedure that induces the [false] belief that drinking will be biochemically verified; e.g., Botvin, Botvin, Renick, Filazzola, & Allegrante, 1984 xClose
Botvin, E.M., Botvin, G.J., Renick, N.L., Filazzola, A.D., & Allegrante, J.P. (1984). Adolescents’ self-reports of tobacco, alcohol, and marijuana use: Examining the comparability of video tape, cartoon and verbal bogus-pipeline procedures. Psychological Reports, 55, 379-386.; Campanelli, Dielman, & Shope, 1987 xClose
Campanelli, P.C., Dielman, T.E., & Shope, J.T. (1987). Validity of adolescents’ self-reports of alcohol use and misuse using a bogus pipeline procedure. Adolescence, 22, 7-22.; Jones & Sigall, 1971 xClose
Jones, E.E., & Sigall, H. (1971). The bogus pipeline: A new paradigm for measuring affect and attitude. Psychological Bulletin, 76, 349-364.) can increase the accuracy of self-reports of alcohol consumption in clinical or research settings.
Physical activity levels are also commonly estimated in cancer prevention studies. Reporting levels of physical activity is challenging for several reasons. Respondents are asked to recall many separate events over a period of time, some of which may not be particularly salient or memorable (e.g., walking). Recall is also more difficult when respondents report both duration and intensity of each activity. In addition, the categories of physical activities defined in surveys (e.g., the Seven Day Activity Recall questionnaire; Sallis, Buono, Roby, Micale & Nelson, 1993 xClose
Sallis, J.F., Buono, M.J., Roby, J.J., Micale, F.G., & Nelson, J.A. (1993) Seven-day recall and other physical activity self-reports in children and adolescents. Medicine and Science in Sport and Exercise, 25, 99-108.) require respondents to make judgments about what constitutes moderate, hard, and very hard activities. Sallis and colleagues (1993) xClose
Sallis, J.F., Buono, M.J., Roby, J.J., Micale, F.G., & Nelson, J.A. (1993) Seven-day recall and other physical activity self-reports in children and adolescents. Medicine and Science in Sport and Exercise, 25, 99-108. found lower reliability for repeated reports from longer intervals (4–6 days between interviews) versus shorter intervals, suggesting rapid decay of subjects’ ability to remember specific physical activities.
There are a number of approaches to objectively assess the validity of self reports of physical activity, including: mechanical or electronic monitors (including accelerometers and heart rate monitors), energy expenditure (including doubly labeled water and calorimeter), measures of fitness, and direct observations (Kohl, Fulton & Caspersen, 2000 xClose
Kohl, H.W., Fulton, J.E., & Caspersen, C.J. (2000). Assessment of physical activity among children and adolescents: A review and synthesis. Preventive Medicine, 31, S54-S76.). These types of measures, however, correlate rather weakly with self-report (Sallis & Saelens, 2000 xClose
Sallis, J.F., & Saelens, B.E. (2000). Assessment of Physical Activity by Self-Report: Status, Limitation and Future Directions. Research Quarterly for Exercise and Sports, 71(2), S1–S14.), although this weak relationship may be due in part to devices such as accelerometers missing some light and moderate activities (Richardson, Leon, Jacobs, Ainsworth & Serfass, 1995 xClose
Richardson, M.T., Leon, A.S., Jacobs, D.R., Jr., Ainsworth, B.E., & Serfass, R. (1995). Ability of Caltrac accelerometer to assess daily physical activity levels. Journal of Cardiopulmonary Rehabilitation, 15, 107–113.). Similarly, self-reported data on physically demanding activities are well-validated using heart-rate monitors, but lower correlations between self-reported physical activity and heart rate have been found for less intensive activities (Janz, Golden, Hansen & Mahoney, 1992 xClose
Janz, K.F., Golden, J.C., Hansen, J.R., & Mahoney, L.T. (1992). Heart rate monitoring of physical activity in children and adolescents: The Muscatine study. Pediatrics, 89, 256–261.). Overall, reliance on the accuracy of physical activity reports may be acceptable for specific activity frequencies (e.g., frequency of tennis) or gross activity (e.g., sedentary versus not), but far less reliable for any specific intensity measure (e.g., total time spent exercising, percent of activity at VO2max, etc).
There is a long history of research relating cancers to dietary factors (e.g., Doll & Peto, 1981 xClose
Doll, R., & Peto, R. (1981). The causes of cancer: Quantitative estimates of available risks of cancer in the United States today. Journal of the National Cancer Institute, 66, 1191-1308.), but evidence for a causative role of diet in most cancers is limited. That is, epidemiological studies have identified relationships between dietary practice and cancer development, but prospective or interventional studies have often not provided strong corroborative support. High-fat diets appear associated with increased risks of breast, colon, prostate, and endometrial cancers (USDHHS, 1988 xClose
U.S. Department of Health and Human Services. (1988). The surgeon general’s report on nutrition and health. Washington, DC: Department of Health and Human Services, Public Health Service, 88-50210.). Diets high in salt and red/processed meats have been linked with stomach and colorectal cancer, respectively (Key, Allen, Spencer, & Travis, 2002 xClose
Key, T. J., Allen, N. E., Spencer, E. A., & Travis, R. C. (2002). The effect of diet on risk of cancer. The Lancet, 360, 861-868.). In contrast, high fiber diets are related to reduced risk of colon cancer (Trock Lanza, & Greenwald, 1990 xClose
Trock, B., Lanza, E., & Greenwald, P. (1990). Dietray fiber, vegetables, and colon cancer: Critical review and meta-analysis of the epidemiologic evidence. Journal of the National Cancer Institute, 82, 650-661.). Unfortunately, there is no established gold standard for the measurement of diet or nutrition, leaving self-report methods open to include daily or weekly diaries, clinical interviews, and portion-size estimates. The latter approach is less frequently used and appears to offer little incremental validity to diet-related risk assessments (Paiva, Amaral, & Barros, 2004 xClose
Paiva, I., Amaral, T., & Barros, H. (2004). Influence of individually estimated portion size on the assessment of nutritional risk in colorectal cancer in Portugal. Journal of Human Nutrition and Dietetics, 17(6), 529-536.). Much research has employed food frequency questionnaires (FFQs), which ask respondents to indicate their "usual" food intake over a weekly, monthly, or yearly reference period (e.g., Zulkifli & Yu, 1992 xClose
Zulkifli, S.N., & Yu, S.M. (1992). The food frequency method for dietary assessment. Journal of American Diet Associations, 92, 681–685.). Cavadini and colleagues (1999) xClose
Cavadini, C., Decarli, B., Dirren, H., Cauderay, M., Narring, F., & Michaud, P.A. (1999). Assessment of adolescent food habits in Switzerland. Appetite, 32, 97-106. found good agreement between an FFQ and "diet records" collected by experience sampling methods (see later section), although the level of agreement varies widely by type of food. However, diet records are not consistently in good agreement with an objective measure such as doubly labeled water (a method in which participants drink treated water that allows for measuring metabolic rate over days or weeks; Livingstone et al., 1992 xClose
Livingstone, M.B.E., Prentice, A.M., Coward, W.A., Strain, J.J., Black, A.E., Davies, P.S.W., et al. (1992). Validation of estimates of energy intake by weighed dietary record and diet history in children and adolescents. American Journal of Clinical Nutrition, 56, 29–35.). Indeed, studies have found substantial underreporting of food intake in diet records among obese participants, female endurance athletes, and adolescents (Schoeller, 1995 xClose
Schoeller, D.A. (1995). Limitations in the assessment of dietary energy intake by self-report. Metabolism, 44, 18–22.). These studies suggest that diet records themselves should not be used as independent methods of validation of FFQs. Other studies have found 24-hour recalls obtained via interview with a dietician provide more accurate estimates (e.g., Field et al., 1998 xClose
Field, A.E., Colditz, G.A., Fox, M.K., Byers, T., Serdula, M., Bosch, R.J., et al. (1998). Comparison of 4 questionnaires for assessment of fruit and vegetable intake. American Journal of Public Health, 88, 1216-1218.; Frank et al., 1992 xClose
Frank, G.C., Nicklas, T.A., Webber, L.S., Major, C., Miller, J.F., & Berenson, G.S. (1992). A food frequency questionnaire for adolescents: Defining eating patterns. Journal of the American Dietetics Association, 92, 313–318.; Rockett et al., 1997 xClose
Rockett, H.R.H., Breitenbach, M., Frazier, A.L., Witschi, J., Wolf, A.M., Field, A.E., et al. (1997). Validation of a youth/adolescent food frequency questionnaire. Preventive Medicine, 26, 808–816.).
Obesity is an established risk factor for some cancers (colon, breast, endometrial, and possibly other cancers; e.g., Trentham-Dietz, Nichols, Hampton, & Newcomb, 2006 xClose
Trentham-Dietz, A., Nichols, H.B., Hampton, J.M., & Newcomb, P.A. (2006). Weight change and risk of endometrial cancer. International Journal of Epidemiology, 35, 151-158.; Verreault, Brisson, Deschenes, & Naud, 1989 xClose
Verreault, R., Brisson, J., Deschenes, L. & Naud, F. (1989). Body weight and prognostic indicators in breast cancer: Modifying effect of estrogen receptors. American Journal of Epidemiology, 129, 260-268.), making it important to accurately assess obesity and body fat distribution. Body mass index (BMI), or the ratio of weight to height, is often reported in epidemiological research. Although there is a tendency for overestimation of height and underestimation of weight, there is evidence for the validity of BMI self-reports (e.g., Palta, Prineas, Berman, & Hannan, 1982 xClose
Palta, M., Prineas, R.J., Berman, R., & Hannan, P. (1982). Comparison of self-reported and measured height and weight. American Journal of Epidemiology, 115, 223-230.). Body fat distribution is measured in a variety of ways, but one easily implemented measure is waist-to-hip circumference, also referred to as waist-to-hip ratio (WHR). Weaver and colleagues (1996) xClose
Weaver, T.W., Kushi, L.H., McGovern, P.G.., Potter, J.D., Rich, S.S., King, R.A., et al. (1996). Validation study of self-reported measures of fat distribution. International Journal of Obesity, 20, 644-650. found that WHR can be measured accurately by self-report when respondents are provided with all the materials needed to conduct the measurements and are given explicit instructions and training. Even under these more optimal conditions, however, women with larger WHR are likely to underestimate their measurements when compared with clinic-based assessments (Weaver et al., 1996 xClose
Weaver, T.W., Kushi, L.H., McGovern, P.G.., Potter, J.D., Rich, S.S., King, R.A., et al. (1996). Validation study of self-reported measures of fat distribution. International Journal of Obesity, 20, 644-650.).
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