Background
In Australia, obesity is a national health priority, and approximately one quarter of young adult Australians are overweight or obese [
1]. This is a concern for immediate social and health problems, as well as risk of future obesity in adulthood and associated chronic health problems, such as type II diabetes, cardiovascular diseases, musculoskeletal disease and some cancers [
1]. Data on prevalence and trends in obesity in young people are needed to inform, monitor, and evaluate appropriate policy and interventions.
Body mass index (BMI) is widely used as a measure of obesity due to its simple derivation from height and weight. Height and weight are commonly self-reported in population health surveys for ease of collection [
2]. In contrast to direct measurement, self-report enables a large number of individuals to be sampled at relatively minimal cost, time, and resources and the survey tool can be administered face to face, by telephone or online.
Self-reported height and weight may be affected by response or recall bias. It is commonly found that weight is underestimated while height is often overestimated [
3‐
8], leading to underestimation of BMI [
5,
7,
8]. Some studies have identified a greater discrepancy in self-reported and measured height and weight among certain groups, including overweight or obese individuals compared to healthy or underweight individuals [
6,
7,
9‐
12], females [
7‐
9,
12,
13], dieters compared to non-dieters, non-smokers compared to smokers [
11,
14], and older individuals [
7,
9,
11]. Such systematic error may lead to lower prevalence estimates of overweight and obesity and systematic bias in studies examining the relationship between obesity and health outcomes dependent on self-reported measurements. In the Australian context, from a telephone-recruited population survey in Adelaide, classification of overweight/obesity among 18–24 year olds was 6.3% through self-report data and 10.1% through measured data,[
13]; while in the 1995 Australian National Health Survey, classification of overweight/obesity among 15–19 year olds was 18% and 12% of males and females, respectively, through self-report data and 25% and 19% of males and females, respectively, through measured data [
6].
In spite of these findings, there remains a lack of data reporting the willingness and accuracy of young people to self-report height, weight, and derived BMI, particularly in community-based settings. Traditional methods of recruiting young people into population surveys, such as random digit dialling and school-based recruitment, are subject to increasing barriers affecting participation, tracking, and retention, such as high mobility, changes in telephone use and technology, and non-school attendance [
15,
16]. Community-based recruitment provides an alternative means to recruit large numbers of young people, and we have previously shown how periodic recruitment from a music festival can be used for surveillance in young people [
17,
18]. In this setting, use of self-reported measurements would be preferable, given the substantial added time and resources required to independently measure participants.
Here we use participants in a risk behaviour survey to determine the accuracy of self-reported height and weight in Australian 16–29 year olds in a community-based setting. Specifically, the aims of this study were:
1)
To determine whether young people participating in a risk behaviour survey are able and willing to provide self-reported height and weight data; and
2)
To assess the accuracy of self-reported height, weight and BMI compared to measured values in a community-based sample of young people.
Results
In total, 1405 questionnaires were completed (see Figure
1). Self-reported height was unknown in 237 (18%) and missing in 28 (2%) questionnaires; self-reported weight was unknown in 148 (11%) and missing in 13 (1%) questionnaires. Overall, 1059 (75%) participants self-reported both height and weight. Comparatively, females, 16–19 year olds, those without post-high school education, those who live with their parents, and those who did not live with a partner were significantly more likely than their counterparts to have self-reported height and/or weight unknown or missing (all p<0.01)( Table
1).
Table 1
Comparison of participant characteristics and risk behaviours by self-report height and weight status
TOTAL
| 1059 | 75 | 346 | 25 | |
Sex
| | | | |
<0.01
|
Male | 436 | 82 | 99 | 19 | |
Female | 623 | 72 | 247 | 28 | |
Median age (IQR)
| 19.7 | (18.0-22.9) | 18.3 | (17.1-20.7) |
<0.01
|
16-19 | 558 | 70 | 240 | 30 | |
20-29 | 501 | 83 | 106 | 17 |
Post high-school education
2
| | | | |
<0.01
|
Yes | 485 | 80 | 122 | 20 | |
No | 561 | 72 | 219 | 28 | |
Lives with parent/s
| | | | |
<0.01
|
Yes | 669 | 72 | 266 | 28 | |
No | 369 | 83 | 77 | 17 | |
Lives with partner
| | | | |
<0.01
|
Yes | 125 | 87 | 19 | 13 | |
No | 912 | 74 | 324 | 26 | |
Recreational income
3
| | | | | 0.10 |
<$120 per week | 703 | 74 | 245 | 26 | |
≥$120 per week | 331 | 78 | 92 | 22 | |
Area of residence
4
| | | | | |
Major city | 697 | 75 | 232 | 25 | 0.88 |
Non-major city | 316 | 75 | 103 | 25 | |
Eighty survey participants had height and weight independently measured. Amongst survey participants providing self-reported height and weight, participants with (6%) and without (94%) independent anthropometric measurement did not differ by demographic characteristics (all p≥0.08).
The final sample is based on 67 participants with complete self-reported and measured height and weight (Figure
1); 51% were male, the median age was 20.1 years, 37% had post-high school education, 67% lived in a major-city, 57% lived with their parent(s), and 58% had $120 or less recreational income per week.
Accuracy of self-reported height, weight, and BMI compared to measured values
As a continuous variable, self-reported and measured height did not significantly differ overall (p=0.06), but mean self-reported height was 2.3 cm less than mean measured height among females (p=0.01) (Table
2). Median self-reported weight was two kilos less than median measured weight (p<0.01). When stratified by age group, sex, and obesity classification, self-reported weight remained significantly lower than measured weight in all sub-categories with the exception of males. Self-reported BMI did not differ from measured BMI overall or when stratified.
Table 2
Comparison of measured and self-reported values for height, weight, and BMI overall and by sex, age group, and obesity classification
Total
| (n=67 ) | Height (cm) | 173.7 (9.8) | 175.0 | 172.7 (11.9) | 174.0 | 0.94 | 0.06 |
Weight (kg) | 72.0 (14.7) | 70.2 | 70.1 (14.5) | 68.0 | 0.96* |
<0.01*
|
BMI (kg/m2) | 23.7 (3.2) | 23.2 | 23.4 (3.2) | 23.0 | 0.84 | 0.16 |
Sex
| Males (n=34) | Height (cm) | 180.2 (7.5) | 180.0 | 180.5 (8.5) | 180.0 | 0.94 | 0.66 |
Weight (kg) | 80.2 (14.0) | 78.8 | 79.2 (13.2) | 80.0 | 0.92* | 0.28* |
BMI (kg/m2) | 24.6 (3.3) | 24.5 | 24.2 (2.8) | 23.3 | 0.85 | 0.21 |
Females (n=33) | Height (cm) | 166.9 (6.9) | 165.0 | 164.6 (9.3) | 164.0 | 0.84 |
0.01
|
Weight (kg) | 63.6 (9.9) | 63.1 | 60.8 (8.8) | 60.0 | 0.93 |
<0.01
|
BMI (kg/m2) | 22.8 (2.9) | 22.0 | 22.5 (3.4) | 21.1 | 0.82 | 0.44 |
Age group (years)
| 16-19 (n=33 ) | Height (cm) | 173.6 (11.0) | 172.0 | 172.4 (13.6) | 172.0 | 0.92 | 0.22 |
Weight (kg) | 70.2 (14.7) | 68.0 | 68.1 (14.6) | 65.0 | 0.94* |
0.01*
|
BMI (kg/m2) | 23.1 (2.9) | 22.0 | 22.8 (3.1) | 22.6 | 0.76 | 0.39 |
20-29 (n=34 ) | Height (cm) | 173.8 (8.7) | 175.8 | 172.9 (10.2) | 175.5 | 0.96 | 0.10 |
Weight (kg) | 73.8 (14.6) | 73.3 | 72.1 (14.4) | 70.5 | 0.96 |
0.01
|
BMI (kg/m2) | 24.3 (3.4) | 24.7 | 23.9 (3.3) | 24.3 | 0.89 | 0.23 |
Obesity classification
| Non-overweight1 (n=43) | Height (cm) | 172.4 (9.2) | 172.0 | 171.3 (10.9) | 172.0 | 0.92 | 0.22 |
Weight (kg) | 65.1 (9.6) | 66.0 | 64.0 (10.4) | 64.0 | 0.96 | 0.05 |
BMI (kg/m2) | 21.8 (1.8) | 21.9 | 21.7 (2.4) | 21.6 | 0.81* | 0.16* |
Overweight/obese2 (n=24) | Height (cm) | 176.1 (10.6) | 177.5 | 175.1 (13.4) | 179.5 | 0.96 | 0.15 |
Weight (kg) | 84.5 (13.9) | 83.5 | 81.1 (14.6) | 80.0 | 0.93 |
<0.01
|
BMI (kg/m2) | 27.1 (2.1) | 26.2 | 26.3 (2.3) | 25.9 | 0.40* | 0.14* |
Correlations between self-reported and measured values for height and weight were high (Table
2); correlation was equal to or greater than 0.92 for all values and sub-categories with the exception of height among females, with correlation of 0.84. Correlation of self-reported and measured BMI was moderately high for all sub-groups with the exception among overweight or obese individuals, in which correlation was only 0.40.
Overall, 52% of participants accurately self-reported their height (within 2cm), 30% under-reported, and 18% over-reported their height (Table
3). There was a tendency for more males than females to over-report their height (p=0.16).
Table 3
Proportion of participants who accurately, under- and over-reported their height and weight stratified by sex, age group, and obesity classification
Height | | Overall | 35 | 52 | 20 | 30 | 12 | 18 | |
Sex | Males | 17 | 50 | 8 | 24 | 9 | 26 | 0.16 |
Females | 18 | 55 | 12 | 36 | 3 | 9 |
Age group (years) | 16-19 | 16 | 48 | 10 | 30 | 7 | 21 | 0.72 |
20-29 | 19 | 56 | 10 | 29 | 5 | 15 |
Obesity classification | Non-overweight5
| 22 | 54 | 11 | 27 | 8 | 20 | 0.79 |
| Overweight/obese6
| 13 | 50 | 9 | 35 | 4 | 15 |
Weight | | Overall | 23 | 34 | 35 | 52 | 9 | 13 | |
Sex | Males | 15 | 44 | 12 | 35 | 7 | 21 |
0.01
|
Females | 8 | 24 | 23 | 70 | 2 | 6 |
Age group (years) | 16-19 | 13 | 39 | 16 | 48 | 4 | 12 | 0.74 |
20-29 | 10 | 29 | 19 | 56 | 5 | 15 |
Obesity classification | Non-overweight5
| 17 | 41 | 18 | 44 | 6 | 15 | 0.24 |
Overweight/obese6
| 6 | 23 | 17 | 65 | 3 | 12 |
Overall, 34% of participants accurately self-reported their weight (within 2 kg), 52% under-reported and 13% over-reported their weight (Table
3). Significantly more females (70%) than males (35%) under-reported their weight by at least two kilograms (p=0.01). Compared to non-overweight participants, overweight/obese participants were less likely to accurately report weight and more likely to under-report weight, but this was non-significant (p=0.24).
In total, 3 (9%) males and 9 (27%) females inaccurately self-reported their height by five centimetres or more (p=0.05), and 12 (35%) males and 5 (15%) females inaccurately self-reported their weight by five kilograms or more (p=0.06). Overweight/obese participants were more likely to misreport their weight by at least 5kg than non-overweight participants (42% vs 15%, p=0.01).
Classification of overweight/obesity
Based on self-report data, 22 (33%) participants were classified as overweight or obese, compared to 26 (39%) participants based on measured data (p=0.29). In total, 59 (88%) were correctly classified. The sensitivity of self-reported data was 77% (95%CI 56%-91%) and specificity was 95% (95%CI 83%-99%).
Discussion
In this study of young people attending a music festival, we determined the feasibility and accuracy of collecting self-reported height and weight. Our results confirm that at a group level, self-report measures in a community-based setting is a useful tool for estimating the prevalence of overweight and obesity, particularly when impractical to take independent measurements.
Three-quarters of survey participants provided both self-report height and weight. In the remainder, the majority reported not knowing their height and/or weight, with only a few missing values, although the “don’t know” category might have also included some refusals. Of concern, participants who did not self-report their height or weight were systematically different from those who did; they were more likely to be female, younger, and less educated. Because height and weight measurements were not taken for all participants, we could not determine whether self-reporting height and weight was influenced by bodyweight status. Further research is needed to explore if there are biases in bodyweight status influencing willingness and ability to self-report height and weight in a community-based setting.
Self-reported and measured height did not significantly differ, and approximately half of males and females reported their height within two centimetres of measured height. However, females were more likely than males to underreport their height, and approximately one quarter of females misreported their height by more than five centimetres, compared to only nine percent of males. Previous studies have observed over-report of height [
6,
7] or decreased accuracy of height with increasing age, perhaps due to decreasing opportunities to regularly measure height or changes in height over time [
4,
27]. Of note, we did not detect a difference in accurate report by age group in our study.
The difference between self-reported and measured weight was more pronounced than for height, particularly among females and overweight or obese individuals. Although one third of all individuals reported their weight within two kilograms of measured weight, a notable 35% of males and 15% of females misreported their weight by five or more kilograms. Females were more likely than males to under-report their weight. Our results are consistent with previous studies reporting systematic under-reporting of weight by females and overweight/obese individuals [
4,
12]. It has been postulated that social desirability bias may explain the underreporting of weight, particularly among females and overweight/obese individuals [
8,
28]. However, other research that has included a measure of social desirability has challenged this notion [
26,
28].
In this study we found that self-report height and weight is a reasonable predictor of overweight and obesity among young people, particularly when pertaining to population-level applications such as monitoring trends in overweight, program evaluation, and advocacy for funding [
12]. Notwithstanding inaccuracies in the self-reporting of weight, the effect on BMI was small, with the median difference less than one unit. Sensitivity of classification of overweight/obesity was around 77% − similar to the 70% found in 15–19 year olds participants of the Australian National Health Survey [
6]. Nonetheless, in this sample, approximately two-fifths of overweight/obese individuals would have been incorrectly classified as non-overweight based on self-report (false negatives), which is consistent with previous findings [
12]. Methods to limit this inaccuracy and bias might include a correction algorithm to account for generalised misreporting based on certain characteristics [
2,
11,
29], periodically measuring a sub-sample, or where feasible, advising participants ahead of time to weigh and measure themselves before participating [
30].
Obesity prevention and control is a national priority in Australia, with increasing millions of dollars being invested to its cause [
31]. Community-based settings, including web-based studies, are ideal alternatives to traditional means of population-based recruitment in order to both inform and evaluate obesity interventions – particularly among young adults who are difficult to access through household telephone surveys and school settings. They provide novel means to reach a large number of people, including hard-to-reach populations [
32]. In these settings self-reported anthropometric measures are the most practical means to define and estimate the prevalence of overweight and obesity. To our knowledge, this is the first study to investigate accuracy of self-report in a community-based sample; our findings confirm that it is possible to use self-report data to estimate and monitor trends in prevalence of overweight and obesity, particularly when bias is expected to remain constant.
This study has a number of limitations. First, the results are based on a convenience-sample and may not be representative of young people in Australia. Second, the sample size for the independent measurement of height and weight was relatively small and may have limited our ability to detect differences and associations with self-reported height and weight. This sample size was limited by the use of only one measuring station, and in the future we recommend more stations are utilised to obtain a larger sample. Third, small differences in self-reported and measured values may be attributable to non-differential measurement bias; multiple researchers were responsible for taking measurements throughout the day and the recruitment day was characterised by high temperatures, reaching up to 40 degrees Celsius. Some participants may have been dehydrated while others were drinking large quantities of water (the study team was distributing water); both factors may have impacted on the accurate measurement of weight. Natural daily weight fluctuation may also partly explain some weight discrepancies; at the festival measurements were taken between 10am-3pm, which may differ to participants’ customary time for weighing themselves. Fourth, selection bias may have been introduced because individuals were not systematically randomised to have their height and weight measured by a researcher; there was potential unrecognised selection bias by the investigators inviting participants to be measured, as well in participants who declined to be measured. However, no demographic differences were identified between those with and without measurements taken. Further research is needed to confirm findings in a larger sample and to see whether a convenience music festival audience differs from the general young adult population in terms of self-reported weight and height accuracy.
Acknowledgments
MH receives funding from the NH&MRC; AP is supported by a VicHealth fellowship; RFP is supported by an Australian Postgraduate Award and a Monash/BakerIDI Departmental Scholarship; MSCL receives funding from an NH&MRC early career research fellowship. The 2011 survey was funded by the Victorian Department of Health. The authors gratefully acknowledge the contribution to this work of the Victorian Operational Infrastructure Support Program. The authors thank Bianca Fiebeger for allowing us to recruit at the Big Day Out music festival, the trained study recruiters, and the study participants. Showbag contents were donated by the Victorian Department of Justice, Marie Stopes International, Youth Projects, Hepatitis Victoria, Department of Health and Ageing, the Free Condom Project and Cadbury Schweppes.
Competing interest
The authors declare that they have no competing interests.
Authors’ contributions
The following co-authors have contributed to the work: AB in data collection, data analysis, manuscript preparation and manuscript review; AP in study design, manuscript preparation and manuscript review; MG in data analysis and manuscript review; RFP in manuscript preparation and manuscript review; MSCL in study design and manuscript review; MH in study design, manuscript preparation and manuscript review. All authors read and approved the final manuscript.