Abstract
Any systematic errors in self-reported height, a measure commonly used in health research, may produce biased BMI estimates and reduce the effectiveness of public health interventions. To our knowledge, none of the studies evaluating the validity of self-reported height explore this issue in cross-national settings. This study analyses data on a sub-set of 750 individuals with information on self-reported and measured height from the Life in Transition Survey (LITS) conducted in 34 European and Central Asian countries in 2016. We make use of the unique design of LITS in which all respondents reported their height, but in one randomly selected primary sampling unit in each country the actual height was also measured, using a portable stadiometer. In addition to analysing individual-level characteristics, using a multiply imputed dataset for missing data and multilevel mixed-effects regressions, we test if macro-level factors are associated with respondents under- or over-reporting their height. We find that on the aggregate level self-reported and measured height estimates are not statistically different, but some socio-demographic groups such as women and those who live in rural areas are likely to overestimate their height. Adjusting for this bias would lead to the higher estimates of the proportion of individuals who are overweight and obese. The results from multilevel analysis also show that macro-level factors do not per se explain the likelihood of misreporting height, but rather some of the effects of individual characteristics are moderated by income inequality.
Highlights
Quality of self-reported data on individuals' height has implications for social epidemiology and public health
In the Results section we show that macro-level factors do not per se explain the likelihood of misreporting height, but rather some of the effects of individual characteristics are moderated by income inequality
To investigate the effect of country-level characteristics, we use two variables widely employed in comparative social and health research – income inequality measured by net Gini coefficients derived from the Standardised World Income Inequality Database (Solt, 2016) and the level of economic development measured by GDP PPP per capita derived from the World Bank (2017)
Summary
Quality of self-reported data on individuals' height has implications for social epidemiology and public health. Since a large share of data on height in demographic, social, and health surveys are based on individuals' declarations (Guilcher et al, 2017; Utter et al, 2018), any systematic errors in this measure may produce biased BMI estimates and reduce the effectiveness of public health campaigns that aim to raise awareness of obesity risks. Self-reported height in most cases is believed to be a quite accurate indicator of actual height (Elgar et al, 2005; Nakamura et al., 1999; Stewart, 1982), some studies find that individuals are likely to over-report their height by as much as 6.9 cm (Brener et al, 2003; Spencer et al, 2002). It is speculated that since height is often linked to higher status, those in the higher ranks of social hierarchy, men, want to be associated with this desired physical feature (Toma et al, 2008)
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