In this study, we examined the bias in reporting of height and weight in Australia using large nationally representative population health survey data. Consistent with a systematic review in 2007  and an earlier study in Australia , we found a tendency for men and women to overestimate their height and to underestimate their weight, thus resulting in an underestimation of BMI. The direction of the bias was consistent with that reported in previous studies [2, 7, 8].
We found that the bias in self-reported BMI (derived from height and weight) has decreased in Australia between 1995 and 2008. Examination of age- and gender-specific effects suggested that the decline is due to more accurate reporting of both height and weight across most sectors of the population. The exception was in the reporting of height among young men, whose average reporting error was similar in 1995 and 2007-2008 at approximately 0.5 cm, an amount consistent with the rounding up of height in centimeters.
Since reporting error is highly dependent on measured BMI, and measured BMI has increased in Australia between 1995 and 2008, we might have expected reporting error to have increased over this period. Instead the converse has been found - the average reporting error in BMI in 1995 was -1.2 units for men and -1.4 for women; in 2007-2008 it had decreased to -0.6 and -0.7 units, respectively.
Using 2007-2008 data, we found the major determinants of the reporting bias to be age, sex, measured BMI, and school education level. Neither the increasing trend in BMI in Australia nor the increased proportion of participants to have completed year 12 at school can explain the diminishing reporting bias between 1995 and 2008, since the signs of both these coefficients were negative.
The diminishing reporting bias observed in this study strongly suggests that there has been an improvement in awareness of personal height and weight across the Australian adult population. Obesity is a National Health Priority Area  in Australia, and in recent years there has been increased coverage of obesity issues in the media , including high profile public health campaigns, such as the "Measure Up" campaign .
There are very few studies across different countries with which to compare our results. However, the observed diminishing bias in Australia is contrary to a recent study that found reporting error in the United States remained constant between 1976 and 2005 but increased in Canada between 1986 and 2005 . There may be differences in the temporal change in reporting bias across countries, in the same way that reporting bias itself may be affected by ethnicity or country-specific factors . Indeed, country-specific factors may contribute to the large variation in reporting bias among studies included in a recent systematic review .
Another factor that may affect the change in reporting bias in different countries is the preferred units in which participants give their self-reported height and weight. Australia moved to a metric system in 1976, and participants in the earlier survey (and older participants in particular) are more likely to have reported height and weight in imperial units, which may be subject to different rounding than if metric units were used . By comparison, in the United States, which has retained the imperial system of measurement, there was no change in reporting bias observed in national surveys between 1976 and 2005.
Despite the improvement in accuracy of reporting BMI, estimates of the prevalence of obesity in Australia in 2007-2008 from self-reported data were underestimated by approximately 4%. This underestimation is driven mainly by older age groups (> 60 years) whose reporting of height, in particular, was much less accurate than younger people.
Using 2007-2008 data we derived two correction methods to adjust for the reporting bias, using age, sex, and self-reported data as covariates. In internal validation, we showed that use of separate correction equations for height and weight were able to provide accurate estimates of the population prevalence of each BMI category and appeared to be more accurate than directly correcting self-reported BMI. The equations for height explained a much greater proportion of the measurement error than those for weight. We have been unable to test the correction equations in an independent population, but if collection of self-reported height and weight is similar to NHS methodology and if the age of the participants is known, we would expect the correction equations to perform very well.
The major strength of this study is that it is based on very recent large nationally representative surveys, in which the use of person weights allows us to infer the results to the entire adult population of Australia. Additionally, we have examined reporting bias across different age and sex strata and have been able to derive correction equations incorporating age and gender. Although there has been some debate as to whether correction equations are useful and reliable , our results suggest that when height and weight are adjusted separately, the corrected estimates of obesity and overweight prevalence at a population level and for age/sex subgroups are very close to those determined from measured data. A spreadsheet version of the correction equations, implemented in Excel, may be downloaded from http://www.health.usyd.edu.au/heconomics/resources/supplementary.php.
There are some limitations to our study. Our results may be affected by slight differences in collection methods between surveys in 1995 and 2007-2008. For example, in the 1995 NNS survey, measured data were determined up to three weeks after the determination of self-reported data from the NHS , whereas in 2007-2008, measurements were taken on the same day as self-reported information was provided.
In both surveys, participants were supplied with information prior to interview stating that there would be a request to take height, weight, hip, and waist measurements. Hence, the lower reporting bias observed in 2007-2008 compared to 1995 cannot be attributed to differences in knowledge that physical measurements would be taken.
With respect to determinants of reporting bias, we were unable to investigate the effect of race or ethnicity (which was significant in US populations ) as ethnicity is not collected in the NHS. Finally, the correction equations for height and weight were accurate in their predictions of true overweight and obesity prevalence at a population level, but at an individual patient level, there is limited improvement in misclassification of BMI category, and hence they should be used with caution for individual prediction.
There are implications of the observed change in reporting bias in Australia for transferability of the results and for projections of trends in obesity. First, our correction equations, although valid for current (2007-2008) data, may not be valid for older surveys or for surveys in the future. This could be investigated when the next NHS results become available in 2011. Second, predictions of future overweight and obesity in Australia from extrapolation of parametric equations derived from past trends in self-reported data  will be inappropriate because change in reporting bias will affect the apparent increase in self-reported obesity. For example, using measured data, the point increase in population obesity in Australia between 1995 and 2008 was 6.1% (from 18.7% to 24.8%), while the self-reported data suggested it was 10.3% (from 11.1% to 21.4%). Hence, part of the apparent increase in obesity prevalence based on self-reported data is due to the decline in reporting bias. Rising obesity rates in Australia  are a major public health concern, but tracking trends in obesity and overweight using self-reported data may be quite misleading, if, as we have shown here, the reporting bias has changed substantially over time.