DÄ internationalArchive15/2020Misclassification of Self-Reported Body Mass Index Categories

Original article

Misclassification of Self-Reported Body Mass Index Categories

A systematic review and meta-analysis

Dtsch Arztebl Int 2020; 117: 253-60. DOI: 10.3238/arztebl.2020.0253

Freigang, R; Geier, A; Schmid, G L; Frese, T; Klement, A; Unverzagt, S

Background: Overweight and obesity are an increasingly serious public health
problem in Western societies, including Germany. The tendency of overweight and obese people not to classify themselves as such limits the efficacy of information on the health risks of these conditions and lessens the motivation to change behavior accordingly. In this article, we summarize the available study data on the self-perception of weight class. We present and discuss the differences between self-reported body-mass index (BMI) category and the actual category of the BMI when it is calculated from the individual’s measured height and weight.

Methods: We systematically searched the Medline, EMBASE, and Cochrane Library databases in August 2017 for pertinent publications. The study protocol was
published in the PROSPERO register (CRD42017064230). Meta-analyses were
calculable for a number of subgroup analyses.

Results: A total of 50 studies from 25 countries were identified that contained
findings on self-estimation of weight in a total of 173 971 study participants. The percentage of correct self-categorizations of BMI category varied from 16% to 83%, with marked heterogeneity of the population groups studied. In Europe, women overestimated their BMI category three times as often as men (RR: 3.22; 95%
confidence interval: [2.87; 3.62], I2 = 0%). Most erroneous classifications were based on underestimates. Study participants of normal weight were more likely than others to categorize their BMI correctly. In European studies, 50.3–75.8% categorized their BMI correctly. Low socioeconomic status was associated with an incorrect perception of BMI.

Conclusion: The self-assignment of BMI categories is often erroneous, with underestimates being more common than overestimates. Physicians should take particular care to provide appropriate information to persons belonging to groups in which underestimating one’s BMI is common, such as overweight people and men in general.

LNSLNS

Overweight and obesity are a growing global public health problem (1). Epidemiological analyses have projected that overweight will be one of the top 4 global causes of preventable years of life lost in the future, besides hypertension, diabetes, and smoking (2). Already in 2007, the social costs of overweight amounted to 16 billion Pound Sterling in the United Kingdom (corresponding to 1% of their gross national product), with a strong upward trend. According to guideline recommendations on the prevention of myocardial infarction, stroke, and diabetes, physicians should offer lifestyle interventions to their overweight patients (3, 4). The 13th nutrition report of the German Nutrition Society (DGE, Deutsche Gesellschaft für Ernährung e. V.) highlights the need to stop this obesity epidemic in Germany and calls for urgent action (5).

According to the World Health Organization (WHO), in 2016 worldwide 39% of adults were overweight with a body mass index (BMI) of ≥ 25 kg/m2, while 11% of men and 15% of women were obese with a BMI of ≥ 30 kg/m2 (6). The prevalence of obesity is high in Germany. Of the adult population, 54% have a BMI of ≥ 25 kg/m2 and 18% of >30 kg/m2 (7). In the United States, prevalence rates are even higher, with 36% of the population being obese (8).

For weight-loss interventions to be successful, people need to be aware of the fact that they are overweight; without this awareness, a behavioral change is unlikely to happen (9, 10, 11). The agreement between self-perception and measured weight status has already been evaluated in numerous studies on a variety of populations; however, an aggregation of these data for the general adult population is missing.

The aim of this review is to organize the available data from studies on weight perception in adults, to identify areas that need to be addressed in future research, and to provide summarized answers to the following questions:

  • How often is the self-perceived BMI categorization accurate?
  • Is misclassification based on overestimation or underestimation?
  • What groups of persons show good weight self-perception and what groups do not?

To this end, differences between self-reported BMI categories and those calculated from height and weight measurements were compared.

Methods

Search strategy

This systematic review is based on a study protocol (Prospero registration number: CRD42017064230). A search strategy was developed on the basis of the inclusion criteria (Box). Three electronic databases (Medline, Embase, and the Cochrane Library) as well as the references of all systematic reviews were systematically searched in August 2017. Detailed information about the search strategy is provided in the eMethods.

Inclusion criteria
Box
Inclusion criteria

Study selection, data extraction and quality assessment

Two authors (RF, AKG) independently screened all retrieved titles and abstracts as well as the full-text articles of all potentially useful papers and extracted the information specified in the study protocol from them. Study quality was assessed using the QUADAS-2 criteria (12) which were adapted to the aim of our study (eBox). After pilot testing and further modification of the quality criteria, which are based on 4 domains, the quality of each study was assessed. Any unclear decisions were discussed with a third researcher (SU).

Modified quality criteria (QUADAS-2) (<a class=12)" width="250" src="https://img.aerzteblatt.de/eyJidWNrZXQiOiJjZG4uYWVyenRlYmxhdHQuZGUiLCJrZXkiOiJiaWxkZXJcLzIwMjBcLzA1 XC9pbWcyNDM0NTY0MDUuZ2lmIiwiZWRpdHMiOnsicmVzaXplIjp7ImZpdCI6Imluc2lkZSIs IndpZHRoIjoyNTB9fX0=" data-bigsrc="https://img.aerzteblatt.de/eyJidWNrZXQiOiJjZG4uYWVyenRlYmxhdHQuZGUiLCJrZXkiOiJiaWxkZXJcLzIwMjBcLzA1 XC9pbWcyNDM0NTY0MDUuZ2lmIiwiZWRpdHMiOnsicmVzaXplIjp7ImZpdCI6Imluc2lkZSIs IndpZHRoIjoxNDAwfX19" data-fullurl="https://cdn.aerzteblatt.de/bilder/2020/05/img243456405.gif" />
eBox
Modified quality criteria (QUADAS-2) (12)

Statistical analysis

The frequencies of accurate self-perception, underestimation, and overestimation were described using prevalence rates and their 95% confidence intervals [95% CI]. Given non-substantial heterogeneity, these were summarized using a random effects model (Review Manager, version 5.3) and only interpreted in a descriptive manner. Heterogeneity assessment relied on statistical criteria (I2 and p values of the Q test); non-substantial heterogeneity was defined as I2<80%. The causes of heterogeneity were explored using calculated relative risks (RR) or odds ratios (OR), comparing the numbers of accurate self-classification by female and male, normal-weight and over-weight, younger and older participants, and participants with lower and higher socioeconomic status (SES). RR/OR >1 describes a higher prevalence in women, normal-weight and younger participants, and participants with lower socioeconomic status. Age comparisons are based on data of the youngest and oldest reported age cohorts and ORs describing the increased likelihood of occurrence in the presence of an age difference of 10 years. Confounder-adjusted results were given preference in the heterogeneity analyses for age and socioeconomic status and reported as ORs. Subgroup analyses are reported for intercontinental differences, with a significance level of p<0.05. Funnel plots were used to assess the risk of publication bias for at least 10 of the studies included in the meta-analysis.

Results

Altogether, 2747 articles were screened based on title and abstracts; 356 potentially relevant articles were assessed in full text. The 50 studies that met the inclusion criteria (Figure) are described in this systematic review.

Literature search flow diagram
Figure
Literature search flow diagram

Description of the included studies

The studies included in this review are based on surveys conducted in 25 countries. Most studies were carried out in North and South America (16 studies), followed by Africa (12 studies), Europe (9 studies), Asia (8 studies), and Australia plus Polynesia (5 studies).

In the included studies, self-perceived BMI category and measured BMI category were compared for altogether 173 971 participants. Of these, 54% were female; 8 studies included only women and 2 studies only men. The mean age ranged between 21 and 64 years. Only 11 studies were based on representative cross-sectional surveys of the general population of a country or region. The included studies typically targeted groups with a particularly high or low risk of overweight, such as specific age groups or professional groups (for example, dancers, firefighters, patients). A detailed description of other study characteristics is provided in eTable 1.

Characteristics of the included studies
eTable 1
Characteristics of the included studies

Index test and reference test

In the index test, study participants were asked in interviews and questionnaires to self-classify their weight based on at least 3 response options. In the reference test, the BMI of participants was obtained by weighing and measuring them at the survey site; these BMI data were then classified as underweight, normal weight, overweight, or obesity.

Quality assessment

The greatest limitations to study quality are related to applicability when the study sample is not representative of the general population (Table 1). Other limitations result from lack of information about how the index test and/or the reference test were performed; in this situation, only inadequate quality assessment could be performed. Due to the use of more narrow criteria, the quality of the studies is rather underestimated than overestimated.

Results of the quality assessment of included studies
Table 1
Results of the quality assessment of included studies

Study results

Accurate self-classification of BMI category

The proportion of participants with accurate self-perception varies between 16% and 83% (Table 2). Because of this substantial heterogeneity (I2 = 100%, p<0.00001), no meta-analysis was performed.

Summary of the BMI categorization results
Table 2
Summary of the BMI categorization results

High rates of misclassification were associated with:

  • African American descent
  • a non-western lifestyle
  • some of the studied professional groups, such as firefighters and healthcare professionals, as well as
  • older patients with cardiovascular disease, diabetes, or overweight.

Younger participants, by contrast, were usually able to classify their weight with a high level of accuracy, irrespective of their health status and cultural background.

In all 9 European studies, the prevalence rates of accurate BMI categorization were above 50% and in 4 studies at about 75%. Accurate self-perception of weight status was far less common in American (prevalence <50% in 9 of 15 studies) and African studies (prevalence <50% in 6 of 12 studies); in 2 studies representative of the US population and Mexican population, respectively, less than 50% of the participants were able to accurately classify their weight (13, 14).

Overestimation and underestimation of BMI category

Inaccurate weight self-perception can show either as an underestimation or overestimation of the BMI category (Table 2). Given the substantial heterogeneity of the studies, here again it was not reasonable to perform a meta-analysis (each I2 = 100%).

Globally, the underestimation prevalence varies between 8% and 84%. Overestimation, by contrast, was markedly less common and, apart from 2 studies (15, e1), only observed in less than 20% of the participants. In Europe, the prevalence of underestimation was mostly less than 25%, while overestimation was observed in less than 10% of participants. The substantial heterogeneity was not reduced by a subgroup analysis of the representative studies.

Predictors of accurate self-classification of BMI category

The impact of sex (25 studies)

In 17 studies, including all 5 studies conducted in Europe, weight self-perception of women was more likely to be accurate compared to that of men (eFigure 1). Given the substantial heterogeneity, summarizing the results of the studies was not suitable, neither for accurate BMI categorization nor for underestimation. In 15 of 22 studies, men underestimated their BMI category more frequently than women (eFigure 2). In 18 of 21 studies, women overestimated their weight more frequently than men; here, large intercultural differences were noted. European women overestimated their BMI categories three times more frequently than men (RR: 3.22; [2.87; 3.62], I2 = 0%). Australian, Asian, and American studies reported similar results, with substantial heterogeneity of the results in the American and Australian studies. In Africa, by contrast, weight overestimation was significantly less common in women than in men (RR: 0.69; [0.48; 0.99], I2 = 0%) (eFigure 3).

Forest plot for the effect of sex on accurate BMI categorization with subgroups for 5 cont
eFigure 1
Forest plot for the effect of sex on accurate BMI categorization with subgroups for 5 cont
Forest plot for the effect of sex on underestimation of BMI category with subgroups for 5 continents
eFigure 2
Forest plot for the effect of sex on underestimation of BMI category with subgroups for 5 continents
Forest plot for the effect of sex on overestimation of BMI category with subgroups for 5 continents
eFigure 3
Forest plot for the effect of sex on overestimation of BMI category with subgroups for 5 continents

The impact of BMI category (36 studies):

Study participants with normal weight more frequently classified their BMI status accurately compared to overweight or obese participants, but there was substantial heterogeneity among included studies (eFigure 4).

Forest plot for the effect of normal weight or overweight on accurate BMI categorization with subgroups for 5 continents
eFigure 4
Forest plot for the effect of normal weight or overweight on accurate BMI categorization with subgroups for 5 continents

Impact of age (10 studies):

Worldwide, younger participants classify their weight more accurately than older participants (eFigure 5). However, the results of the only German study were strikingly different (16). In the subgroup of normal-weight participants, the youngest surveyed age cohort, the 18- to 29-year-olds, less frequently classified their BMI category correctly compared to the age cohort of the 70- to 79-year-olds (OR 0.23; [0.16; 0.33]). The funnel plot (eFigure 6) showed no sign of publication bias.

Forest plot for the effect of age on accurate BMI categorization with subgroups for continents and the subgroup of exclusively normal-weight participants, *results with confounder adjustment
eFigure 5
Forest plot for the effect of age on accurate BMI categorization with subgroups for continents and the subgroup of exclusively normal-weight participants, *results with confounder adjustment
Funnel plot for the effect of age on accurate BMI categorization
eFigure 6
Funnel plot for the effect of age on accurate BMI categorization

The impact of socioeconomic status (15 studies):

Participants with lower SES, lower educational attainment, or lower income were less likely to classify their BMI status accurately compared to participants with higher SES; again, substantial heterogeneity was observed among the studies (eTable 2).

Influence of socioeconomic status, education, income, and work on accurate BMI categorization
eTable 2
Influence of socioeconomic status, education, income, and work on accurate BMI categorization

Discussion

Our review shows that worldwide people find it difficult to accurately categorize their BMI status, with underestimations being far more common than overestimations. Most at risk of underestimating their BMI category were older, male, and overweight participants as well as participants with low socioeconomic status.

A variety of factors has been discussed as possible causes of inaccurate self-perceived BMI categorization. Besides lack of information, key factors include social group effects which make it appear “normal” to be overweight, because other people living in the same social environment are also overweight—the so-called “peer effect” (3, 13, 17). Such environments can be professional groups, age groups, migrant background, urban/rural settings, cultural groups, or traditions (18). In Germany, overweight is a common and relevant problem: 54% of the adult population has a BMI ≥ 25 kg/m2 and 18% a BMI above 30 kg/m2 (7). A comparison of studies from the United States (19, 20, 21) and Europe (16, 22, 23) suggests that with the increase in prevalence of overweight the likelihood of inaccurate self-perception also increases. Against the backdrop of high obesity rates in Germany (7), raising awareness in a timely manner could help to thwart this effect.

In African cultures, overweight is often seen as a sign of wealth and health, and being underweight as a sign of a potential HIV infection or AIDS (24, 25, 26). At the same time, in some of the included African studies, e.g. the study by Phetla et al. (24), the percentage of overweight participants was very high.

Underestimation of the BMI category was markedly more common than overestimation in almost all studies, a finding that confirms the relevance of raising awareness of overweight/obesity in the general population.

Due to the high variability of the results of the individual studies, no significant differences between men and women could be demonstrated. However, in more than two-thirds of the studies allowing direct comparison, women were ahead in terms of accurate self-perception. In addition, marked differences in the type of misclassification of BMI category were found. While women rather overestimated their BMI category in most cultures, the primary concern in men was underestimation of the BMI category. This is in line with the results of the representative German Health Interview and Examination Survey for Adults (16) which found that, while the rates of accurate self-perceived BMI categorization were similar for the two sexes, inaccurately classifying men showed a trend to underestimate their weight, while their female counterparts were prone to overestimating their weight. The authors attributed this to greater social pressure associated with the prevailing thin ideal among women, while men follow another, more muscular body ideal (16).

A higher risk of inaccurate self-perception was confirmed for older participants. A representative European study on persons aged 60 years and older found that older participants in this cohort too were more prone to inaccurate self-perception, especially underestimation. As possible explanations, the authors suggested the peer effect and decreasing susceptibility to body image ideals (15). This result is confirmed by the finding of the German study that the proportion of normal-weight persons perceiving themselves as “too fat” declined with age (16).

Medical advice should take into account that overweight and obese individuals and persons with low social status frequently underestimate their BMI category. Information about overweight/obesity and associated health risks falls on deaf ears if patients do not identify themselves as belonging to the risk group (11, 27). A nationally representative US study showed that overweight and obese adults who underestimated their BMI category were less likely to have an interest in weight loss or to have made attempts at weight loss in the preceeding year (28).

Consequently, establishing patient awareness and readiness for change should precede any lifestyle intervention for weight loss (9); if any misperceptions are identified, these should be corrected (11). Long-term primary care appears to be ideal for interventions requiring gradual development of problem awareness, repeated raising of the issue, and cultural sensitivity. Knowing about the prevalence of BMI misperceptions is valuable to primary care physicians as it prevents them from coming straight to the point without adequate preparation (3). In modern practice teams, the task of giving advice to these patients can be delegated to non-medical healthcare professionals who are highly efficient in providing this service and relieve the burden on the physician (29). It appears to be backed by solid evidence that it is worth the effort for the patient, practice team, and society (30).

Limitations

The limitations of our review result from the diversity of research questions addressed in the various studies included. Not only are the study populations very different from each other, but the studies also vary widely in terms of aim or focus (e.g. physical activity [e2], diet [e3, e4], or co-morbidities [e5, e6]). This results in a very heterogeneous presentation of the endpoints selected by us, some of which were not the primary outcomes of the studies. Some of the included studies compared data of different groups of participants, e.g. laymen versus hospital staff (e7), high versus low social status (e8), or untrained individuals versus athletes (e9). We pooled the data of these groups and included them in our analyses without further adjustments. Our subgroup analyses are limited to sex, BMI category, the continent where the study was conducted, and study-specific age and socioeconomic status categories. Confounder adjustment was only performed for age and socioeconomic status. In view of the applicability of numerous studies to the European context, it should be noted that nationally representative US studies investigate populations with overweight prevalence rates of about 70% (13), whereas in most European countries, including Germany, the prevalence rates are considerably lower (16). Additional studies from Europe and Germany, especially nationally representative surveys, are required to gain a better understanding of the relevance of this issue and shape everyday doctor–patient contacts accordingly.

Conflict of interest statement
The authors declare that no conflict of interest exists.

Manuscript received on 30 May 2019; revised version accepted on
6 January 2020

Translated from the original German by Ralf Thoene, MD.

Corresponding author
PD Dr. rer. nat. Susanne Unverzagt
Selbstständige Abteilung für Allgemeinmedizin
Medizinische Fakultät der Universität Leipzig
Philipp-Rosenthal-Straße 55
04103 Leipzig, Germany
susanne.unverzagt@medizin.uni-leipzig.de

Cite this as:
Freigang R, Geier AK, Schmid GL, Frese T, Klement A, Unverzagt S: Misclassification of self-reported body mass index categories—a systematic review and meta-analysis. Dtsch Arztebl Int 2020; 117: 253–60. DOI: 10.3238/arztebl.2020.0253

Supplementary material

For eReferences please refer to:
www.aerzteblatt-international.de/ref1520

eMethods, eTables:
www.aerzteblatt-international.de/20m0253

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e18.
Faber M, Kruger HS: Dietary intake, perceptions regarding body weight, and attitudes toward weight control of normal weight, overweight, and obese Black females in a rural village in South Africa. Ethn Dis 2005; 15: 238–45.
e19.
Gao C, Lv X, Yin Y, et al.: Perceptions and behaviours towards high body weight among adults in Northeast China. Public Health Nutr 2017; 20: 1557–63 CrossRef MEDLINE
e20.
Harris CL, Strayhorn G, Moore S, Goldman B, Martin MY: Perceived physician-informed weight status predicts accurate weight self-perception and weight self-regulation in low-income, African American Women. J Health Care Poor Underserved 2016; 27: 1441–63 CrossRef MEDLINE
e21.
Hendley Y, Zhao L, Coverson DL, et al.: Differences in weight perception among blacks and whites. J Womens Health (Larchmt) 2011; 20: 1805–11 CrossRef MEDLINE PubMed Central
e22.
Herbert J, Peterson KL, Alston L, Allender S, Nichols M: Comparison between measured and perceived weight status in a nationally representative sample of Australian adults. Obes Res Clin Pract 2017; 11: 414–25 CrossRef
e23.
Howard NJ, Hugo GJ, Taylor AW, Wilson DH: Our perception of weight: Socioeconomic and sociocultural explanations. Obes Res Clin Pract 2008; 2: 71–142 CrossRef MEDLINE
e24.
Jáuregui Lobera I, Bolaños-Ríos P, Valero-Blanco E, Ortega-de-la-Torre Á: Eating attitudes, body image and risk for eating disorders in a group of Spanish dancers. Nutr Hosp 2016; 33: 588 CrossRef MEDLINE
e25.
Jeffs E, Haszard JJ, Sharp B, Gullam J, Paterson H: Pregnant women lack accurate knowledge of their BMI and recommended gestational weight gain. N Z Med J 2016; 129: 37–45.
e26.
Johnston DW, Lordan G: Weight perceptions, weight control and income: An analysis using British data. Econ Hum Biol 2014; 12: 132–9 CrossRef MEDLINE
e27.
Kim S, So W-Y: Secular trends in the prevalence of weight misperception among Korean adults, 2001–2013. Obes Res Clin Pract 2018; 12: 346–50 CrossRef MEDLINE
e28.
Loret de Mola C, Pillay TD, Diez-Canseco F, Gilman RH, Smeeth L, Miranda JJ: Body mass index and self-perception of overweight and obesity in rural, urban and rural-to-urban migrants: PERU MIGRANT study. PLoS ONE 2012; 7: e50252 CrossRef MEDLINE PubMed Central
e29.
Maruf FA, Akinpelu AO, Nwankwo MJ: Perceived body image and weight: Discrepancies and gender differences among University undergraduates. Afr Health Sci 2012; 12: 464–72 CrossRef MEDLINE PubMed Central
e30.
Minsky S, Vreeland B, Miller M, Gara M: Concordance between measured and self-perceived weight status of persons with serious mental illness. Psychiatr Serv 2013; 64: 91–3 CrossRef MEDLINE
e31.
Mogre V, Abedandi R, Salifu ZS: Distorted self-perceived weight status and underestimation of weight status in diabetes mellitus type 2 patients. PLoS ONE 2014; 9: e95165 CrossRef MEDLINE PubMed Central
e32.
Mogre V, Aleyira S, Nyaba R: Misperception of weight status and associated factors among undergraduate students. Obes Res Clin Pract 2015; 9: 466–74 CrossRef MEDLINE
e33.
Muhihi AJ, Njelekela MA, Mpembeni R, Mwiru RS, Mligiliche N, Mtabaji J: Obesity, overweight, and perceptions about body weight among middle-aged adults in Dar es Salaam, Tanzania. ISRN Obes 2012; 2012: 368520 CrossRef MEDLINE PubMed Central
e34.
Peltzer K, Pengpid S: Body weight and body image among a sample of female and male South African University Students. Gender & Behaviour 2012; 10: 4509–22.
e35.
Prinsloo EAM, Joubert G, Mohale M, et al.: The prevalence and perception of obesity and its association with the lifestyle of women at the Mangaung University Community Partnership Project healthcare centre, Bloemfontein. South African Family Practice 2014; 53: 366–72 CrossRef
e36.
Rahman M, Berenson AB: Self-perception of weight and its association with weight-related behaviors in young, reproductive-aged women. Obstet Gynecol 2010; 116: 1274–80 CrossRef MEDLINE PubMed Central
e37.
Shin J, Choi Y, Han K-T, et al.: The combined effect of subjective body image and body mass index (distorted body weight perception) on suicidal ideation. J Prev Med Public Health 2015; 48: 94–104 CrossRef MEDLINE PubMed Central
e38.
Sinhababu A: A study on weight status and weight perception of GNM students of a nursing training centre, Bankura, West Bengal. J Indian Med Assoc 2007; 105: 85–7.
e39.
van Minnen K, Davis WA, Bruce DG, Davis TME: Accuracy, determinants, and consequences of body weight self-perception in type 2 diabetes: The Fremantle Diabetes Study. J Diabetes Complicat 2011; 25: 1–6 CrossRef MEDLINE
* The two authors are co-first authors.
Department of General Practice, Faculty of Medicine, University of Leipzig, Leipzig: Romy Freigang, Dr. med. Anne-Kathrin Geier, M. Sc. in Public Health, Dr. med. Gordian Lukas Schmid,
PD Dr. rer. nat. Susanne Unverzagt
Institute of General Practice and Family Medicine, Martin Luther University Halle-Wittenberg, Halle: Romy Freigang, Dr. med. Gordian Lukas Schmid, Prof. Dr. med. Thomas Frese,
Prof. Dr. med. Andreas Klement, PD Dr. rer. nat. Susanne Unverzagt
Inclusion criteria
Box
Inclusion criteria
Literature search flow diagram
Figure
Literature search flow diagram
Key messages
Results of the quality assessment of included studies
Table 1
Results of the quality assessment of included studies
Summary of the BMI categorization results
Table 2
Summary of the BMI categorization results
Modified quality criteria (QUADAS-2) (12)
eBox
Modified quality criteria (QUADAS-2) (12)
Forest plot for the effect of sex on accurate BMI categorization with subgroups for 5 cont
eFigure 1
Forest plot for the effect of sex on accurate BMI categorization with subgroups for 5 cont
Forest plot for the effect of sex on underestimation of BMI category with subgroups for 5 continents
eFigure 2
Forest plot for the effect of sex on underestimation of BMI category with subgroups for 5 continents
Forest plot for the effect of sex on overestimation of BMI category with subgroups for 5 continents
eFigure 3
Forest plot for the effect of sex on overestimation of BMI category with subgroups for 5 continents
Forest plot for the effect of normal weight or overweight on accurate BMI categorization with subgroups for 5 continents
eFigure 4
Forest plot for the effect of normal weight or overweight on accurate BMI categorization with subgroups for 5 continents
Forest plot for the effect of age on accurate BMI categorization with subgroups for continents and the subgroup of exclusively normal-weight participants, *results with confounder adjustment
eFigure 5
Forest plot for the effect of age on accurate BMI categorization with subgroups for continents and the subgroup of exclusively normal-weight participants, *results with confounder adjustment
Funnel plot for the effect of age on accurate BMI categorization
eFigure 6
Funnel plot for the effect of age on accurate BMI categorization
Characteristics of the included studies
eTable 1
Characteristics of the included studies
Influence of socioeconomic status, education, income, and work on accurate BMI categorization
eTable 2
Influence of socioeconomic status, education, income, and work on accurate BMI categorization
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e20.Harris CL, Strayhorn G, Moore S, Goldman B, Martin MY: Perceived physician-informed weight status predicts accurate weight self-perception and weight self-regulation in low-income, African American Women. J Health Care Poor Underserved 2016; 27: 1441–63 CrossRef MEDLINE
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e24.Jáuregui Lobera I, Bolaños-Ríos P, Valero-Blanco E, Ortega-de-la-Torre Á: Eating attitudes, body image and risk for eating disorders in a group of Spanish dancers. Nutr Hosp 2016; 33: 588 CrossRef MEDLINE
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e27.Kim S, So W-Y: Secular trends in the prevalence of weight misperception among Korean adults, 2001–2013. Obes Res Clin Pract 2018; 12: 346–50 CrossRef MEDLINE
e28.Loret de Mola C, Pillay TD, Diez-Canseco F, Gilman RH, Smeeth L, Miranda JJ: Body mass index and self-perception of overweight and obesity in rural, urban and rural-to-urban migrants: PERU MIGRANT study. PLoS ONE 2012; 7: e50252 CrossRef MEDLINE PubMed Central
e29.Maruf FA, Akinpelu AO, Nwankwo MJ: Perceived body image and weight: Discrepancies and gender differences among University undergraduates. Afr Health Sci 2012; 12: 464–72 CrossRef MEDLINE PubMed Central
e30.Minsky S, Vreeland B, Miller M, Gara M: Concordance between measured and self-perceived weight status of persons with serious mental illness. Psychiatr Serv 2013; 64: 91–3 CrossRef MEDLINE
e31.Mogre V, Abedandi R, Salifu ZS: Distorted self-perceived weight status and underestimation of weight status in diabetes mellitus type 2 patients. PLoS ONE 2014; 9: e95165 CrossRef MEDLINE PubMed Central
e32.Mogre V, Aleyira S, Nyaba R: Misperception of weight status and associated factors among undergraduate students. Obes Res Clin Pract 2015; 9: 466–74 CrossRef MEDLINE
e33.Muhihi AJ, Njelekela MA, Mpembeni R, Mwiru RS, Mligiliche N, Mtabaji J: Obesity, overweight, and perceptions about body weight among middle-aged adults in Dar es Salaam, Tanzania. ISRN Obes 2012; 2012: 368520 CrossRef MEDLINE PubMed Central
e34.Peltzer K, Pengpid S: Body weight and body image among a sample of female and male South African University Students. Gender & Behaviour 2012; 10: 4509–22.
e35.Prinsloo EAM, Joubert G, Mohale M, et al.: The prevalence and perception of obesity and its association with the lifestyle of women at the Mangaung University Community Partnership Project healthcare centre, Bloemfontein. South African Family Practice 2014; 53: 366–72 CrossRef
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e37.Shin J, Choi Y, Han K-T, et al.: The combined effect of subjective body image and body mass index (distorted body weight perception) on suicidal ideation. J Prev Med Public Health 2015; 48: 94–104 CrossRef MEDLINE PubMed Central
e38.Sinhababu A: A study on weight status and weight perception of GNM students of a nursing training centre, Bankura, West Bengal. J Indian Med Assoc 2007; 105: 85–7.
e39.van Minnen K, Davis WA, Bruce DG, Davis TME: Accuracy, determinants, and consequences of body weight self-perception in type 2 diabetes: The Fremantle Diabetes Study. J Diabetes Complicat 2011; 25: 1–6 CrossRef MEDLINE