Article

The Validity of Obesity Based on Self-reported Weight and Height: Implications for Population Studies*

Skaraborg Institute, Skovde, Sweden.
Obesity (Impact Factor: 4.39). 02/2007; 15(1):197-208. DOI: 10.1038/oby.2007.536
Source: PubMed

ABSTRACT To validate self-reported information on weight and height in an adult population and to find a useful algorithm to assess the prevalence of obesity based on self-reported information.
This was a cross-sectional survey consisting of 1703 participants (860 men and 843 women, 30 to 75 years old) conducted in the community of Vara, Sweden, from 2001 to 2003. Self-reported weight, height, and corresponding BMI were compared with measured data. Obesity was defined as measured BMI > or = 30 kg/m2. Information on education, self-rated health, smoking habits, and physical activity during leisure time was collected by a self-administered questionnaire.
Mean differences between measured and self-reported weight were 1.6 kg (95% confidence interval, 1.4; 1.8) in men and 1.8 kg (1.6; 2.0) in women (measured higher), whereas corresponding differences in height were -0.3 cm (-0.5; -0.2) in men and -0.4 cm (-0.5; -0.2) in women (measured lower). Age and body size were important factors for misreporting height, weight, and BMI in both men and women. Obesity (measured) was found in 156 men (19%) and 184 women (25%) and with self-reported data in 114 men (14%) and 153 women (20%). For self-reported data, the sensitivity of obesity was 70% in men and 82% in women, and when adjusted for corrected self-reported data and age, it increased to 81% and 90%, whereas the specificity decreased from 99% in both sexes to 97% in men and 98% in women.
The prevalence of obesity based on self-reported BMI can be estimated more accurately when using an algorithm adjusted for variables that are predictive for misreporting.

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    • "The smoking and drinking variables were then dummy coded using the " not at all " category as the reference group. Finally, following standard procedures (Nyholm et al., 2007), responses to an overall self-rated general health questionnaire item (5-point scale from very good to very bad) were dummy coded using the lowest health rating as the reference group. "
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    ABSTRACT: Individuals often overestimate their height while concomitantly underestimating their weight; this results in lower obesity prevalence rates when self-report data are used to calculate BMI, a pattern that has been observed in both sexes (Gorber et al., 2007; Nyholm et al., 2007). This misclassification of obesity due to inaccurate self-reported (SR) BMI values has considerable public health implications, especially given that global obesity levels have reached epidemic-proportions. Thus, accurately identifying obese individuals, in particular, is crucial to the interpretation of lifestyle factors that increase obesity risk (Flegal et al., 2013). Individual characteristics, such as true (measured) weight and age, also appear to influence the accuracy of SR BMI values. It appears that actual body weight may influence the extent to which an individual underestimates their weight. For example, Hill and Roberts (1998) documented a ~0.1 increase in BMI underestimation for every unit increase in measured BMI. Furthermore, previous research has documented that the overestimation of height and underestimation of weight significantly increases with age, leading to the increased misclassification of overweight and obese older individuals (Lawlor et al., 2002; Dahl et al., 2010). This misclassification may preclude enrollment in weight reduction programs designed to reduce the health complications associated with obesity, thereby putting these older individuals at risk. Still, studies assessing the accuracy of SR BMI have largely been restricted to wealthier nations. The few studies examining these relationships in lower income countries have produced conflicting results. Weight underestimation and height overestimation (similar to Western populations) has been documented in Mexico, Thailand, and China (Santillan and Camargo, 2003; Lim et al., 2009; Zhou et al., 2010), while studies in Brazil and Mexico have observed no significant difference between self-report and measured BMI (Osuna-Ramírez et al., 2006; Rech et al., 2008). Thus, further work is required to determine if the discrepancies between SR and measured BMI are shared or differ by culture. The present study assesses whether SR and measured BMI values differ cross-culturally in older adults using data from World Health Organization's Study on global AGEing and adult health (SAGE) Wave 1 (Kowal et al., 2012). Data from six middle income countries (China, Ghana, India, Mexico, the Russian Federation, and South Africa) are used to examine how discrepancies in SR and actual BMI among older adults varies cross-culturally. Three hypotheses are tested. First, BMI calculated from SR height and weight will significantly differ from BMI calculated from height and weight measured by SAGE interviewers. Second, heavier individuals will be more likely to underreport their weight, decreasing their SR BMI value and resulting in a negative difference between SR and measured BMI. Third, age will be inversely correlated with discrepancies in SR and measured BMI (calculated by subtracting measured BMI from SR BMI); thus, older adults will be more likely to misreport their height and weight).
    Population Association of America 2015 Annual Meeting, San Diego, CA, USA; 05/2015
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    • "The strengths of our study were that participants were randomly selected from the population and that weight and height were measured. It has previously been demonstrated that self-reported weight is increasingly underestimated with increasing BMI (Nyholm et al., 2007), with the likely impact of misclassification in lower categories of BMI. We also acknowledge some limitations in our study: we relied on self-reports to identify lifestyle factors and exposure to medications and diseases, and there is the possibility of differential recall influenced by emotions and wellbeing. "
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    ABSTRACT: Objective: To examine the cross-sectional association between overweight and obesity and positive and negative affect. Method: Participants included 273 women, aged 29–84 years, who were enrolled in the Geelong Osteoporosis Study (GOS). Weight and height were measured and overweight and obesity determined from body mass index (BMI; kg/m2) according to WHO criteria. Medical history and lifestyle exposures were assessed by questionnaire. Positive and negative affect scores were derived using the validated 20-item Positive and Negative Affect Schedule (PANAS) and categorised into tertiles. Results: A pattern of greater negative affect scores was observed for increasing levels of BMI. Setting normal weight as the referent category, the odds for having a negative affect score in the highest tertile were sequentially increased for women who were overweight (OR = 1.31, 95% CI: 0.72–2.40) and obese (OR = 1.95, 95% CI: 1.02–3.73). The associa- tion between obesity and increased negative affect was diminished by adjusting for physical illness (adjusted OR = 1.76, 95% CI: 0.91–3.42). These associations were not substantially influenced by positive affect score or other exposures. No association was detected between BMI categories and positive affect scores. Conclusions: We report data suggesting that obesity is associated with greater negative affect scores, reflecting emotions such as distress, anger, disgust, fear and shame, and that this association is attenuated by physical illness. Further investigations are now warranted to explore possible mechanistic interplay between pathological, neurobiological and psychosocial factors.
    Australian and New Zealand Journal of Psychiatry 03/2013; 00:1-6. DOI:10.1177/0004867413483371 · 3.77 Impact Factor
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    • "With regard to adiposity assessment, the majority of the included studies used self-reported BMI (see Table 1). In spite of evidence that measured and self-reported BMIs are highly correlated [47], systematic self-reporting biases have been documented and are associated with underestimates of obesity [72]. Although BMI is a crude estimate of total body fat, other investigators have found that emotional factors are more strongly related to fat accumulation in particular regions, such as centrally located adiposity, than to total adiposity [21] [73]. "
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    ABSTRACT: Taken in isolation, depression, anxiety, and hostility/anger have been shown to predict obesity. It is unknown whether these negative emotional factors are associated with adiposity, independently of each other. The objective of this review was to determine whether negative emotional factors have independent associations with adiposity. We searched for observational studies examining adiposity and two or more negative emotional factors. Studies which examined a negative emotional factor using analyses which controlled for other emotional factor(s) were selected for the review. Three prospective and 11 cross-sectional studies met our inclusion/exclusion criteria. Of these investigations, 64% indicated that depression had positive associations with adiposity, independent of anxiety or hostility, and 56% indicated that anxiety had independent associations with adiposity. Only 33% of studies found independent associations for hostility and adiposity; however, far fewer studies were available. Depression and anxiety have independent associations with excess adiposity when controlling for other emotional factors. Additional studies are needed to determine whether hostility/anger is independently associated with excess adiposity. These results have implications for the design of effective obesity prevention programs.
    Journal of psychosomatic research 10/2012; 73(4):243-50. DOI:10.1016/j.jpsychores.2012.07.009 · 2.84 Impact Factor
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