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The high and increasing1 prevalence of overweight (Body Mass Index [BMI] ≥25 kg/m2) and obesity (BMI ≥30 kg/m2) threaten public health in New Zealand and worldwide.2,3BMI (weight [kg]/ height [m2]) is the measure most often used to determine the prevalence of obesity, identify groups at risk of increased morbidity and to evaluate the efficacy of interventions.4 However, BMI is limited by its inability to quantify body composition and failure to indicate the distribution of body fat.4 Despite this, BMI performs well as a predictor of disease risk, showing graded associations with metabolic risk and/or mortality in most populations,5,6including in Māori and Pacific people.7-9A 2010 review10 found that BMI and measures of central obesity (e.g. waist circumference, waist to hip ratio, and waist to height ratio) are similarly related to cardiovascular disease, hypertension and diabetes in most populations (with the possible exception of Asians). Consequently, despite its limitations, it has been argued that BMI remains a highly useful measure of adiposity.11,12BMI measures derived from self-reported height and weight (referred to as ‘self-reported BMI') are a practical and cost effective way of collecting data from large geographically dispersed populations.4,13 However, reliance on self-reported BMI measures is controversial, as self-reported height and weight can be subject to substantial measurement error.14According to a systematic review of 64 studies published between 1979 and 2005,15 older respondents tend to overestimate height and the majority of respondents underestimate weight. Bias in self-reported height and weight has been found to vary by ethnicity,13,16 degree of overweight13,16-21 and level of education.13,22These biases mean that substantial misclassification can occur when self-reported data are used to assign participants to BMI categories.13 However, deviations of self-reported from measured BMI are small, and rarely exceed 2 BMI units.13 Therefore, the use of self-reported BMI as a continuous measure may give reasonably accurate estimates of health risks associated with excess body weight,13,17 even if self-reported BMI measures underestimate the population prevalence of overweight and obesity based on usual BMI cutoffs.To our knowledge, only one study has examined the agreement between self-reported and measured BMI in a New Zealand population. Using data collected in 1982, Stewart et al21compared the self-reported and measured height, weight and derived BMI of 1,598 Auckland Caucasians aged 35-65 years. Men and women tended to overestimate height and underestimate weight, with overall mean differences of 1.94 cm for height (95%CI 1.78, 2.10) and -0.58 kg for weight (95%CI -0.75, -0.41), resulting in an overall mean difference in BMI of -0.77 kg/m2(95%CI -0.84, -0.68).Height overestimation was greater in men (2.14 cm vs. 1.60 cm in women, p <0.001), and in both sexes was greater in the older age groups (p <0.001). The validity of weight estimation did not differ by sex or age group, however underestimation increased as body weight increased (mean differences in increasing weight quartiles were 0.08, -0.63, -0.59, -0.93 kg for males, and -0.18, -0.67, -0.49, -1.34 kg for females).In order to accurately assess the prevalence of obesity and the impact of weight management interventions in New Zealand, more research is needed on the agreement of self-reported and measured BMI. Since more recent national surveys have not included collection of both self-reported and measured data,23,24 this study uses data from the 1989/1990 Life in New Zealand Survey (LINZ)25 to examine the agreement between self-reported and measured height, weight and BMI, and between BMI categorisation based on self-reported and measured data.Given the significant limitation of the age of the dataset, analysis has been limited to one age group identified in many studies as being at particularly high risk of weight gain: 40-50 year olds.26-30Method Sample—The Life in New Zealand (LINZ) Survey was a nationwide cross-sectional health, nutrition, leisure and physical activity survey conducted in 1989/1990. The methods of this survey have been previously described.25 Adults (≥18 years) were recruited by stratified random sampling of the 1988 New Zealand electoral rolls, including the Māori rolls. In Phase I of the survey (April 1989 to March 1990), self-reported data such as age, sex, height, weight, ethnicity, occupation and SES were gathered by postal questionnaires. Participants were unaware at the time of questionnaire completion that height and weight would subsequently be measured. In Phase II, participants from 20 electorates considered to be representative of the country (in terms of urban-rural composition) were selected for health checks. Health checks were conducted between June and August 1989 and included detailed anthropometric measurements. Participant height without shoes was measured to the nearest millimetre using a calibrated stadiometer. Weight without shoes or heavy clothing was measured to the nearest 0.1 kg. A correction factor of 0.5 kg was subtracted from measured weights to take into account the light clothing worn by participants. BMI was calculated for each participant from measured height and weight. Data analysis—Measured BMI values were used to classify participants as underweight (<18.5 kg/m2) normal weight (18.5-24.99 kg/m2), overweight (25-29.99 kg/m2) and obese (≥30 kg/m2) according to the World Health Organization criteria.31 SES was measured on a 6-point scale (1=highest, 6=lowest) using self-reported information on employment, qualifications and household income.25 SES categories 1 and 2, and 4 to 6 were collapsed to produce three SES categories. Participants could indicate identification with more than one ethnic group and were assigned to one of five ethnicity categories prioritized as follows: New Zealand Māori, Cook Island Māori, Samoan, ‘Other', and finally New Zealand European. The classification of ethnicity in the present study is different to that in the original LINZ analyses, where New Zealand Māori was prioritized and all other participants classified as ‘Other New Zealanders'.32 Statistical analysis—Difference scores for height, weight and BMI were calculated by subtracting measured values from self-reported values. Means for self-reported and measured values were compared using paired sample t-tests. Difference scores for BMI were plotted against the mean of self-reported and measured values in a Bland Altman plot.33 Limits of agreement were calculated as mean difference ± 1.96 standard deviations of the difference. BMI categories based on self-reported and measured data were cross-tabulated, and linear weighted kappa statistics calculated to determine degree of concordance. Multiple linear regression analysis was used to evaluate whether age, sex, ethnicity, SES and measured BMI category were independently associated with the difference between measured and self-reported BMI. All analyses were undertaken using Stata software (version 12).34 Results Response rates to the LINZ survey were approximately 80% for Phase I questionnaires and 56% for Phase II health checks, after taking into account participants who were deceased or away from address at the time of recruitment.32 Phase II response rates were significantly lower in individuals from the Māori electoral rolls (35.5%) than from the General rolls (58.3%).32 Age specific response rates were not available. A total of 346 40-50 year old participants provided both self-reported and measured height and weight. One woman who overestimated weight by 30 kg was excluded as data checking revealed a probable transposition error. The ethnicity and socio-economic status of the sample is displayed in Table 1. Mean (SD) age of participants was 44.1 (3.1) years and 51% of the sample was male. Table 1. Participant ethnicity and Socio-Economic Status of 40-50 year olds in the 1989 LINZ survey (n=345) Characteristic n (%) Ethnicitya NZ European 322 (93.33) NZ Māori 17 (4.93) Other 6 (1.74) Socioeconomic Status b 1-2 114 (34.44) 3 106 (32.02) 4-6 111 (33.53) a Participants could indicate identification with more than one ethnic group and were assigned to one of five ethnicity categories prioritised as follows: New Zealand Māori, Cook Island Māori, Samoan, ‘Other', and finally New Zealand European.32 b SES measured on a 6-point scale (1=highest, 6=lowest) using self-reported information on employment, qualifications and household income.25 Data on SES were not available for 14 participants. Mean differences between self-reported and measured height, weight and BMI for men and women are displayed in Table 2. Self-reported weight was not significantly different from measured weight in men (p=0.905) or women (p=0.129). Height was significantly overestimated in both sexes (men 1.08 cm p<0.001, women 0.61 cm p<0.001), resulting in a small, statistically significant underestimation of BMI in men (-0.31 kg/m² p<0.001) and women (-0.26 kg/m² p<0.001). Table 2. Comparison of measured and self-reported height, weight, and derived body mass index in middle-aged men and women Characteristic Self-reported Mean (SD) Measured Mean (SD) Mean difference (95% CI) Minimum, maximum differences P value for difference Men (n=177) Height (cm) 176.57 (6.50) 175.48 (6.03) 1.08 (0.58, 1.59) -18.50, 21.1 <0.001* Weight (kg) 82.75 (12.06) 82.74 (12.22) 0.02 (-0.24, 0.27) -6.20, 4.20 0.905 BMI (kg/m2) 26.59 (4.01) 26.90 (4.05) -0.31 (-0.48, -0.14) -5.82, 5.77 <0.001* Women (n=168) Height (cm) 163.56 (5.51) 162.95 (4.92) 0.61 (0.35, 0.87) -5.00, 6.50 <0.001* Weight (kg) 69.19 (14.62) 69.41 (14.92) -0.22 (-0.49, 0.06) -9.80, 10.1 0.129 BMI (kg/m2) 25.90 (5.48) 26.16 (5.58) -0.26 (-0.41, -0.11) -4.67, 4.23 <0.001* BMI categories defined as: underweight <18.5; normal weight 18.5-24.99; overweight 25.0-29.99; obese ≥30.031 *Statistically significant difference, paired t-test Note: Mean difference calculated as self-reported-measured data (positive values therefore indicate overestimation) Figure 1 is a Bland Altman plot33 showing the extent of agreement between measured and self-reported BMI values for sample participants (male and female data combined). Figure 1. Bland Altman plot of the difference between self-reported and measured BMI vs. the mean of self-reported and measured BMI (male and female data combined). The solid line represents the mean difference (-0.29 kg/m²) and the dashed lines represent 95% limits of agreement (-2.40 kg/m² and 1.83 kg/m²). A comparison of classification into BMI categories based on self-reported and measured BMI is shown in Table 3. Overall, 85.3% of men and 92.9% of women were correctly classified into BMI category using self-reported data (linear weighted kappa 0.80 and 0.93 respectively). Table 3. Comparison of classification into body mass index (BMI) categories using measured and self-reported data (n=345) Self-reported BMI (kg/m2) Measured BMI (kg/m2) Total <18.5 18.5-24.9 25-29.9 ≥30.0 Men (n=177) <18.5 0 0 0

Summary

Abstract

Aim

To examine the agreement between self-reported and measured height, weight and BMI in 40-50 year old New Zealand men and women.

Method

Self-reported and measured height, weight and derived BMI were examined using data from 345 40-50 year old participants in the 1989/1990 Life In New Zealand Survey. Factors associated with biased reporting were assessed using regression models.

Results

Height was overestimated by men (1.08 cm, 95%CI 0.58, 1.59 p

Conclusion

Self-reported height and weight from New Zealand 40-50 year olds in 1989 produced BMI estimates valid for use in epidemiological studies, especially when used as a continuous variable. Our analyses need to be replicated using data from a current and representative New Zealand sample.

Author Information

Heidi Sharples, MSc student, Department of Human Nutrition; Peter Crutchley, MSc student, Department of Human Nutrition; Jos 00e9 A Garc 00eda, Lecturer, Department of Preventive & Social Medicine; Andrew Gray, Research Fellow (Biostatistician), Department of Preventive & Social Medicine; Caroline C Horwath, Senior Lecturer, Department of Human Nutrition; University of Otago, Dunedin

Acknowledgements

We thank Professor David Russell, Dr Noela Wilson, Professor Peter Herbison and Associate Professor Winsome Parnell for collecting the Life In New Zealand Survey data used in this study as well as Allison Gabucan, Marcus Dafu Du and Emily Watson (University of Otago) for assistance with data analysis.

Correspondence

Dr Caroline Horwath, Department of Human Nutrition, University of Otago, PO Box 56, Dunedin, New Zealand. Fax: + 64 (03) 4797958

Correspondence Email

caroline.horwath@otago.ac.nz

Competing Interests

None.

Kelly T, Yang W, Chen CS, et al. Global burden of obesity in 2005 and projections to 2030. Int J Obes. 2008;32(9):1431-7.Ministry of Health and University of Auckland. Nutrition and the burden of disease: New Zealand 1997-2011. Wellington: Ministry of Health; 2003.Flegal KM, Graubard BI, Williamson DF, Gail MH. Excess deaths associated with underweight, overweight, and obesity. JAMA. 2005;293(15):1861-7.Gibson RS. Principles of Nutritional Assessment. 2nd ed. Oxford: Oxford University Press; 2005, p259-64.Song X, Pitkaniemi J, Gao W, et al. Relationship between body mass index and mortality among Europeans. Eur J Clin Nutr. 2012;66(2):156-165.Zheng W, McLerran DF, Rolland B, et al. Association between body-mass index and risk of death in more than 1 million Asians. N Engl J Med. 2011;364(8):719-729.Taylor RW, Brooking L, Williams SM, et al. Body mass index and waist circumference cutoffs to define obesity in indigenous New Zealanders. Am J Clin Nutr. 2010;92(2):390-397.Bell AC, Swinburn BA, Simmons D, et al. Heart disease and diabetes risk factors in Pacific Islands communities and associations with measures of body fat. N Z Med J. 2001;114(1131):208-213.Turley M, Tobias M, Paul, S. Non-fatal disease burden associated with excess body mass index and waist circumference in New Zealand adults. Aust NZ J Public Health. 2006;30(3):231-237.Huxley RS, Mendis S, Zheleznyakov E, et al. Body mass index, waist circumference and waist:hip ratio as predictors of cardiovascular risk - a review of the literature. Eur J Clin Nutr. 2010;64(1):16-22.Bouchard C. BMI, fat mass, abdominal adiposity and visceral fat: where is the 'beef'? Int J Obes (Lond). 2007;31(10):1552-1553Gelber RP, Gaziano JM, Orav EJ, et al. Measures of obesity and cardiovascular risk among men and women. J Am Coll Cardiol. 2008;52(8):605-615.Stommel M, Schoenborn CA. Accuracy and usefulness of BMI measures based on self-reported weight and height: findings from the NHANES & NHIS 2001-2006. BMC Public Health. 2009;9:421-31.Rothman KJ. BMI-related errors in the measurement of obesity. Int J Obes. 2008; 32:S56-S59.Gorber S, Tremblay M, Moher D, Gorber B. A comparison of direct vs. self report measures for assessing height weight and body mass index: a systematic review. Obes Rev. 2007;8:307-26.Gillum RF, Sempos CT. Ethnic variation in validity of classification of overweight and obesity using self-reported weight and height in American women and men: the Third National Health and Nutrition Examination Survey. BMC Nutr J. 2005;4:27.Spencer EA, Appleby PN, Davey GK, Key TJ. Validity of self-reported height and weight in 4808 EPIC-Oxford participants. Public Health Nutr. 2002;5(4):561-5.Burton N, Brown W, Dobson A. Accuracy of body mass index estimated from self-reported height and weight in mid-aged Australian women. Aust NZ J Public Health. 2010;34(6):620-3.Wada K, Tamakoshi K, Tsunekawa T, et al. Validity of self-reported height and weight in a Japanese workplace population. Int J Obes (Lond). 2005;29(9):1093-9.Dekkers JC, van Wier MF, Hendriksen IJM, et al. Accuracy of self-reported body weight, height and waist circumference in a Dutch overweight working population. BMC Med Res Methodol. 2008;8:69.Stewart AW, Jackson RT, Ford MA, Beaglehole R. Underestimation of relative weight by use of self-reported height and weight. Am J Epidemiol. 1987;125(1):122-6.Craig BM, Adams AK. Accuracy of body mass index categories based on self-reported height and weight among women in the United States. Matern Child Health J. 2008;13(4):489-96.Parnell WR, Wilson NC, Russell DG. Methodology of the 1997 New Zealand National Nutrition Survey. NZ Med J. 2001;114(1128):123-6.University of Otago and Ministry of Health. Methodology Report for the 2008/09 New Zealand Adult Nutrition Survey. Wellington: Ministry of Health; 2011.Russell DG, Wilson NC. Life in New Zealand Commission Report Volume I: Executive Overview. Dunedin: University of Otago; 1991.Ball K, Crawford D, Ireland P, et al. Patterns and demographic predictors of 5-year weight change in a multi-ethnic cohort of men and women in Australia. Public Health Nutr. 2003;6(3):269-280.Sternfeld B, Wang H, Quesenberry CP, JR et al. Physical activity and changes in weight and waist circumference in midlife women: findings from the Study of Womens Health Across the Nation. Am J Epidemiol. 2004;160(9):912-22.Williams LT, Young AF, Brown WJ. Weight gained in two years by a population of mid-aged women: How much is too much? Int J Obes. 2006;30(8):1229-1233.Nafziger AN, Lindvall K, Norberg M, et al. Who is maintaining weight in a middle-aged population in Sweden? A longitudinal analysis over 10 years. BMC Public Health. 2007;7:108.Rissanen A, Heliovaara M, Aromaa A. Overweight and anthropometric changes in adulthood: a prospective study of 17,000 Finns. Int J Obes. 1988;12(5):391-401.World Health Organisation. Obesity: Preventing and Managing the Global Epidemic: Report on a WHO consultation. Technical Report Series No.854. Geneva: World Health Organization; 2000.Russell DG, Wilson NC, Spears G, Herbison P. Life in New Zealand Commission Report Volume II: Survey Protocol. Dunedin: University of Otago; 1991.Bland JM, Altman DG. Measuring agreement in method comparison studies. Stat Methods Med Res.1999;8(2):135-60.StataCorp. 2011. Stata Statistical Software: Release 12. College Station, TX: StataCorp LP.Landis JR, Koch G. The measurement of observer agreement for categorical data. Biometrics.1977;33:159-74.Katzmarzyk PT, Davis C. Thinness and body shape of Playboy centerfolds from 1978 to 1998. Int J Obes Relat Metab Disord. 2001;25(4):590-592.Leit RA, Pope HG Jr., Gray JJ. Cultural expectations of muscularity in men: the evolution of playgirl centerfolds. Int J Eat Disord. 2001;29(1):90-93.Andreyeva T, Puhl RM, Brownell KD. Changes in perceived weight discrimination among Americans, 1995-1996 through 2004-2006. Obesity (Silver Spring). 2008; 16(5):1129-1134.Stommel M, Osier N. Temporal changes in bias of body mass index scores based on self-reported height and weight. Int J Obes (Lond). 2012. Epub 02/05/2012Department of Statistics. New Zealand Census of population and dwellings 1986.Total population statistics. Wellington: Department of Statistics; 1987.

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The high and increasing1 prevalence of overweight (Body Mass Index [BMI] ≥25 kg/m2) and obesity (BMI ≥30 kg/m2) threaten public health in New Zealand and worldwide.2,3BMI (weight [kg]/ height [m2]) is the measure most often used to determine the prevalence of obesity, identify groups at risk of increased morbidity and to evaluate the efficacy of interventions.4 However, BMI is limited by its inability to quantify body composition and failure to indicate the distribution of body fat.4 Despite this, BMI performs well as a predictor of disease risk, showing graded associations with metabolic risk and/or mortality in most populations,5,6including in Māori and Pacific people.7-9A 2010 review10 found that BMI and measures of central obesity (e.g. waist circumference, waist to hip ratio, and waist to height ratio) are similarly related to cardiovascular disease, hypertension and diabetes in most populations (with the possible exception of Asians). Consequently, despite its limitations, it has been argued that BMI remains a highly useful measure of adiposity.11,12BMI measures derived from self-reported height and weight (referred to as ‘self-reported BMI') are a practical and cost effective way of collecting data from large geographically dispersed populations.4,13 However, reliance on self-reported BMI measures is controversial, as self-reported height and weight can be subject to substantial measurement error.14According to a systematic review of 64 studies published between 1979 and 2005,15 older respondents tend to overestimate height and the majority of respondents underestimate weight. Bias in self-reported height and weight has been found to vary by ethnicity,13,16 degree of overweight13,16-21 and level of education.13,22These biases mean that substantial misclassification can occur when self-reported data are used to assign participants to BMI categories.13 However, deviations of self-reported from measured BMI are small, and rarely exceed 2 BMI units.13 Therefore, the use of self-reported BMI as a continuous measure may give reasonably accurate estimates of health risks associated with excess body weight,13,17 even if self-reported BMI measures underestimate the population prevalence of overweight and obesity based on usual BMI cutoffs.To our knowledge, only one study has examined the agreement between self-reported and measured BMI in a New Zealand population. Using data collected in 1982, Stewart et al21compared the self-reported and measured height, weight and derived BMI of 1,598 Auckland Caucasians aged 35-65 years. Men and women tended to overestimate height and underestimate weight, with overall mean differences of 1.94 cm for height (95%CI 1.78, 2.10) and -0.58 kg for weight (95%CI -0.75, -0.41), resulting in an overall mean difference in BMI of -0.77 kg/m2(95%CI -0.84, -0.68).Height overestimation was greater in men (2.14 cm vs. 1.60 cm in women, p <0.001), and in both sexes was greater in the older age groups (p <0.001). The validity of weight estimation did not differ by sex or age group, however underestimation increased as body weight increased (mean differences in increasing weight quartiles were 0.08, -0.63, -0.59, -0.93 kg for males, and -0.18, -0.67, -0.49, -1.34 kg for females).In order to accurately assess the prevalence of obesity and the impact of weight management interventions in New Zealand, more research is needed on the agreement of self-reported and measured BMI. Since more recent national surveys have not included collection of both self-reported and measured data,23,24 this study uses data from the 1989/1990 Life in New Zealand Survey (LINZ)25 to examine the agreement between self-reported and measured height, weight and BMI, and between BMI categorisation based on self-reported and measured data.Given the significant limitation of the age of the dataset, analysis has been limited to one age group identified in many studies as being at particularly high risk of weight gain: 40-50 year olds.26-30Method Sample—The Life in New Zealand (LINZ) Survey was a nationwide cross-sectional health, nutrition, leisure and physical activity survey conducted in 1989/1990. The methods of this survey have been previously described.25 Adults (≥18 years) were recruited by stratified random sampling of the 1988 New Zealand electoral rolls, including the Māori rolls. In Phase I of the survey (April 1989 to March 1990), self-reported data such as age, sex, height, weight, ethnicity, occupation and SES were gathered by postal questionnaires. Participants were unaware at the time of questionnaire completion that height and weight would subsequently be measured. In Phase II, participants from 20 electorates considered to be representative of the country (in terms of urban-rural composition) were selected for health checks. Health checks were conducted between June and August 1989 and included detailed anthropometric measurements. Participant height without shoes was measured to the nearest millimetre using a calibrated stadiometer. Weight without shoes or heavy clothing was measured to the nearest 0.1 kg. A correction factor of 0.5 kg was subtracted from measured weights to take into account the light clothing worn by participants. BMI was calculated for each participant from measured height and weight. Data analysis—Measured BMI values were used to classify participants as underweight (<18.5 kg/m2) normal weight (18.5-24.99 kg/m2), overweight (25-29.99 kg/m2) and obese (≥30 kg/m2) according to the World Health Organization criteria.31 SES was measured on a 6-point scale (1=highest, 6=lowest) using self-reported information on employment, qualifications and household income.25 SES categories 1 and 2, and 4 to 6 were collapsed to produce three SES categories. Participants could indicate identification with more than one ethnic group and were assigned to one of five ethnicity categories prioritized as follows: New Zealand Māori, Cook Island Māori, Samoan, ‘Other', and finally New Zealand European. The classification of ethnicity in the present study is different to that in the original LINZ analyses, where New Zealand Māori was prioritized and all other participants classified as ‘Other New Zealanders'.32 Statistical analysis—Difference scores for height, weight and BMI were calculated by subtracting measured values from self-reported values. Means for self-reported and measured values were compared using paired sample t-tests. Difference scores for BMI were plotted against the mean of self-reported and measured values in a Bland Altman plot.33 Limits of agreement were calculated as mean difference ± 1.96 standard deviations of the difference. BMI categories based on self-reported and measured data were cross-tabulated, and linear weighted kappa statistics calculated to determine degree of concordance. Multiple linear regression analysis was used to evaluate whether age, sex, ethnicity, SES and measured BMI category were independently associated with the difference between measured and self-reported BMI. All analyses were undertaken using Stata software (version 12).34 Results Response rates to the LINZ survey were approximately 80% for Phase I questionnaires and 56% for Phase II health checks, after taking into account participants who were deceased or away from address at the time of recruitment.32 Phase II response rates were significantly lower in individuals from the Māori electoral rolls (35.5%) than from the General rolls (58.3%).32 Age specific response rates were not available. A total of 346 40-50 year old participants provided both self-reported and measured height and weight. One woman who overestimated weight by 30 kg was excluded as data checking revealed a probable transposition error. The ethnicity and socio-economic status of the sample is displayed in Table 1. Mean (SD) age of participants was 44.1 (3.1) years and 51% of the sample was male. Table 1. Participant ethnicity and Socio-Economic Status of 40-50 year olds in the 1989 LINZ survey (n=345) Characteristic n (%) Ethnicitya NZ European 322 (93.33) NZ Māori 17 (4.93) Other 6 (1.74) Socioeconomic Status b 1-2 114 (34.44) 3 106 (32.02) 4-6 111 (33.53) a Participants could indicate identification with more than one ethnic group and were assigned to one of five ethnicity categories prioritised as follows: New Zealand Māori, Cook Island Māori, Samoan, ‘Other', and finally New Zealand European.32 b SES measured on a 6-point scale (1=highest, 6=lowest) using self-reported information on employment, qualifications and household income.25 Data on SES were not available for 14 participants. Mean differences between self-reported and measured height, weight and BMI for men and women are displayed in Table 2. Self-reported weight was not significantly different from measured weight in men (p=0.905) or women (p=0.129). Height was significantly overestimated in both sexes (men 1.08 cm p<0.001, women 0.61 cm p<0.001), resulting in a small, statistically significant underestimation of BMI in men (-0.31 kg/m² p<0.001) and women (-0.26 kg/m² p<0.001). Table 2. Comparison of measured and self-reported height, weight, and derived body mass index in middle-aged men and women Characteristic Self-reported Mean (SD) Measured Mean (SD) Mean difference (95% CI) Minimum, maximum differences P value for difference Men (n=177) Height (cm) 176.57 (6.50) 175.48 (6.03) 1.08 (0.58, 1.59) -18.50, 21.1 <0.001* Weight (kg) 82.75 (12.06) 82.74 (12.22) 0.02 (-0.24, 0.27) -6.20, 4.20 0.905 BMI (kg/m2) 26.59 (4.01) 26.90 (4.05) -0.31 (-0.48, -0.14) -5.82, 5.77 <0.001* Women (n=168) Height (cm) 163.56 (5.51) 162.95 (4.92) 0.61 (0.35, 0.87) -5.00, 6.50 <0.001* Weight (kg) 69.19 (14.62) 69.41 (14.92) -0.22 (-0.49, 0.06) -9.80, 10.1 0.129 BMI (kg/m2) 25.90 (5.48) 26.16 (5.58) -0.26 (-0.41, -0.11) -4.67, 4.23 <0.001* BMI categories defined as: underweight <18.5; normal weight 18.5-24.99; overweight 25.0-29.99; obese ≥30.031 *Statistically significant difference, paired t-test Note: Mean difference calculated as self-reported-measured data (positive values therefore indicate overestimation) Figure 1 is a Bland Altman plot33 showing the extent of agreement between measured and self-reported BMI values for sample participants (male and female data combined). Figure 1. Bland Altman plot of the difference between self-reported and measured BMI vs. the mean of self-reported and measured BMI (male and female data combined). The solid line represents the mean difference (-0.29 kg/m²) and the dashed lines represent 95% limits of agreement (-2.40 kg/m² and 1.83 kg/m²). A comparison of classification into BMI categories based on self-reported and measured BMI is shown in Table 3. Overall, 85.3% of men and 92.9% of women were correctly classified into BMI category using self-reported data (linear weighted kappa 0.80 and 0.93 respectively). Table 3. Comparison of classification into body mass index (BMI) categories using measured and self-reported data (n=345) Self-reported BMI (kg/m2) Measured BMI (kg/m2) Total <18.5 18.5-24.9 25-29.9 ≥30.0 Men (n=177) <18.5 0 0 0

Summary

Abstract

Aim

To examine the agreement between self-reported and measured height, weight and BMI in 40-50 year old New Zealand men and women.

Method

Self-reported and measured height, weight and derived BMI were examined using data from 345 40-50 year old participants in the 1989/1990 Life In New Zealand Survey. Factors associated with biased reporting were assessed using regression models.

Results

Height was overestimated by men (1.08 cm, 95%CI 0.58, 1.59 p

Conclusion

Self-reported height and weight from New Zealand 40-50 year olds in 1989 produced BMI estimates valid for use in epidemiological studies, especially when used as a continuous variable. Our analyses need to be replicated using data from a current and representative New Zealand sample.

Author Information

Heidi Sharples, MSc student, Department of Human Nutrition; Peter Crutchley, MSc student, Department of Human Nutrition; Jos 00e9 A Garc 00eda, Lecturer, Department of Preventive & Social Medicine; Andrew Gray, Research Fellow (Biostatistician), Department of Preventive & Social Medicine; Caroline C Horwath, Senior Lecturer, Department of Human Nutrition; University of Otago, Dunedin

Acknowledgements

We thank Professor David Russell, Dr Noela Wilson, Professor Peter Herbison and Associate Professor Winsome Parnell for collecting the Life In New Zealand Survey data used in this study as well as Allison Gabucan, Marcus Dafu Du and Emily Watson (University of Otago) for assistance with data analysis.

Correspondence

Dr Caroline Horwath, Department of Human Nutrition, University of Otago, PO Box 56, Dunedin, New Zealand. Fax: + 64 (03) 4797958

Correspondence Email

caroline.horwath@otago.ac.nz

Competing Interests

None.

Kelly T, Yang W, Chen CS, et al. Global burden of obesity in 2005 and projections to 2030. Int J Obes. 2008;32(9):1431-7.Ministry of Health and University of Auckland. Nutrition and the burden of disease: New Zealand 1997-2011. Wellington: Ministry of Health; 2003.Flegal KM, Graubard BI, Williamson DF, Gail MH. Excess deaths associated with underweight, overweight, and obesity. JAMA. 2005;293(15):1861-7.Gibson RS. Principles of Nutritional Assessment. 2nd ed. Oxford: Oxford University Press; 2005, p259-64.Song X, Pitkaniemi J, Gao W, et al. Relationship between body mass index and mortality among Europeans. Eur J Clin Nutr. 2012;66(2):156-165.Zheng W, McLerran DF, Rolland B, et al. Association between body-mass index and risk of death in more than 1 million Asians. N Engl J Med. 2011;364(8):719-729.Taylor RW, Brooking L, Williams SM, et al. Body mass index and waist circumference cutoffs to define obesity in indigenous New Zealanders. Am J Clin Nutr. 2010;92(2):390-397.Bell AC, Swinburn BA, Simmons D, et al. Heart disease and diabetes risk factors in Pacific Islands communities and associations with measures of body fat. N Z Med J. 2001;114(1131):208-213.Turley M, Tobias M, Paul, S. Non-fatal disease burden associated with excess body mass index and waist circumference in New Zealand adults. Aust NZ J Public Health. 2006;30(3):231-237.Huxley RS, Mendis S, Zheleznyakov E, et al. Body mass index, waist circumference and waist:hip ratio as predictors of cardiovascular risk - a review of the literature. Eur J Clin Nutr. 2010;64(1):16-22.Bouchard C. BMI, fat mass, abdominal adiposity and visceral fat: where is the 'beef'? Int J Obes (Lond). 2007;31(10):1552-1553Gelber RP, Gaziano JM, Orav EJ, et al. Measures of obesity and cardiovascular risk among men and women. J Am Coll Cardiol. 2008;52(8):605-615.Stommel M, Schoenborn CA. Accuracy and usefulness of BMI measures based on self-reported weight and height: findings from the NHANES & NHIS 2001-2006. BMC Public Health. 2009;9:421-31.Rothman KJ. BMI-related errors in the measurement of obesity. Int J Obes. 2008; 32:S56-S59.Gorber S, Tremblay M, Moher D, Gorber B. A comparison of direct vs. self report measures for assessing height weight and body mass index: a systematic review. Obes Rev. 2007;8:307-26.Gillum RF, Sempos CT. Ethnic variation in validity of classification of overweight and obesity using self-reported weight and height in American women and men: the Third National Health and Nutrition Examination Survey. BMC Nutr J. 2005;4:27.Spencer EA, Appleby PN, Davey GK, Key TJ. Validity of self-reported height and weight in 4808 EPIC-Oxford participants. Public Health Nutr. 2002;5(4):561-5.Burton N, Brown W, Dobson A. Accuracy of body mass index estimated from self-reported height and weight in mid-aged Australian women. Aust NZ J Public Health. 2010;34(6):620-3.Wada K, Tamakoshi K, Tsunekawa T, et al. Validity of self-reported height and weight in a Japanese workplace population. Int J Obes (Lond). 2005;29(9):1093-9.Dekkers JC, van Wier MF, Hendriksen IJM, et al. Accuracy of self-reported body weight, height and waist circumference in a Dutch overweight working population. BMC Med Res Methodol. 2008;8:69.Stewart AW, Jackson RT, Ford MA, Beaglehole R. Underestimation of relative weight by use of self-reported height and weight. Am J Epidemiol. 1987;125(1):122-6.Craig BM, Adams AK. Accuracy of body mass index categories based on self-reported height and weight among women in the United States. Matern Child Health J. 2008;13(4):489-96.Parnell WR, Wilson NC, Russell DG. Methodology of the 1997 New Zealand National Nutrition Survey. NZ Med J. 2001;114(1128):123-6.University of Otago and Ministry of Health. Methodology Report for the 2008/09 New Zealand Adult Nutrition Survey. Wellington: Ministry of Health; 2011.Russell DG, Wilson NC. Life in New Zealand Commission Report Volume I: Executive Overview. Dunedin: University of Otago; 1991.Ball K, Crawford D, Ireland P, et al. Patterns and demographic predictors of 5-year weight change in a multi-ethnic cohort of men and women in Australia. Public Health Nutr. 2003;6(3):269-280.Sternfeld B, Wang H, Quesenberry CP, JR et al. Physical activity and changes in weight and waist circumference in midlife women: findings from the Study of Womens Health Across the Nation. Am J Epidemiol. 2004;160(9):912-22.Williams LT, Young AF, Brown WJ. Weight gained in two years by a population of mid-aged women: How much is too much? Int J Obes. 2006;30(8):1229-1233.Nafziger AN, Lindvall K, Norberg M, et al. Who is maintaining weight in a middle-aged population in Sweden? A longitudinal analysis over 10 years. BMC Public Health. 2007;7:108.Rissanen A, Heliovaara M, Aromaa A. Overweight and anthropometric changes in adulthood: a prospective study of 17,000 Finns. Int J Obes. 1988;12(5):391-401.World Health Organisation. Obesity: Preventing and Managing the Global Epidemic: Report on a WHO consultation. Technical Report Series No.854. Geneva: World Health Organization; 2000.Russell DG, Wilson NC, Spears G, Herbison P. Life in New Zealand Commission Report Volume II: Survey Protocol. Dunedin: University of Otago; 1991.Bland JM, Altman DG. Measuring agreement in method comparison studies. Stat Methods Med Res.1999;8(2):135-60.StataCorp. 2011. Stata Statistical Software: Release 12. College Station, TX: StataCorp LP.Landis JR, Koch G. The measurement of observer agreement for categorical data. Biometrics.1977;33:159-74.Katzmarzyk PT, Davis C. Thinness and body shape of Playboy centerfolds from 1978 to 1998. Int J Obes Relat Metab Disord. 2001;25(4):590-592.Leit RA, Pope HG Jr., Gray JJ. Cultural expectations of muscularity in men: the evolution of playgirl centerfolds. Int J Eat Disord. 2001;29(1):90-93.Andreyeva T, Puhl RM, Brownell KD. Changes in perceived weight discrimination among Americans, 1995-1996 through 2004-2006. Obesity (Silver Spring). 2008; 16(5):1129-1134.Stommel M, Osier N. Temporal changes in bias of body mass index scores based on self-reported height and weight. Int J Obes (Lond). 2012. Epub 02/05/2012Department of Statistics. New Zealand Census of population and dwellings 1986.Total population statistics. Wellington: Department of Statistics; 1987.

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The high and increasing1 prevalence of overweight (Body Mass Index [BMI] ≥25 kg/m2) and obesity (BMI ≥30 kg/m2) threaten public health in New Zealand and worldwide.2,3BMI (weight [kg]/ height [m2]) is the measure most often used to determine the prevalence of obesity, identify groups at risk of increased morbidity and to evaluate the efficacy of interventions.4 However, BMI is limited by its inability to quantify body composition and failure to indicate the distribution of body fat.4 Despite this, BMI performs well as a predictor of disease risk, showing graded associations with metabolic risk and/or mortality in most populations,5,6including in Māori and Pacific people.7-9A 2010 review10 found that BMI and measures of central obesity (e.g. waist circumference, waist to hip ratio, and waist to height ratio) are similarly related to cardiovascular disease, hypertension and diabetes in most populations (with the possible exception of Asians). Consequently, despite its limitations, it has been argued that BMI remains a highly useful measure of adiposity.11,12BMI measures derived from self-reported height and weight (referred to as ‘self-reported BMI') are a practical and cost effective way of collecting data from large geographically dispersed populations.4,13 However, reliance on self-reported BMI measures is controversial, as self-reported height and weight can be subject to substantial measurement error.14According to a systematic review of 64 studies published between 1979 and 2005,15 older respondents tend to overestimate height and the majority of respondents underestimate weight. Bias in self-reported height and weight has been found to vary by ethnicity,13,16 degree of overweight13,16-21 and level of education.13,22These biases mean that substantial misclassification can occur when self-reported data are used to assign participants to BMI categories.13 However, deviations of self-reported from measured BMI are small, and rarely exceed 2 BMI units.13 Therefore, the use of self-reported BMI as a continuous measure may give reasonably accurate estimates of health risks associated with excess body weight,13,17 even if self-reported BMI measures underestimate the population prevalence of overweight and obesity based on usual BMI cutoffs.To our knowledge, only one study has examined the agreement between self-reported and measured BMI in a New Zealand population. Using data collected in 1982, Stewart et al21compared the self-reported and measured height, weight and derived BMI of 1,598 Auckland Caucasians aged 35-65 years. Men and women tended to overestimate height and underestimate weight, with overall mean differences of 1.94 cm for height (95%CI 1.78, 2.10) and -0.58 kg for weight (95%CI -0.75, -0.41), resulting in an overall mean difference in BMI of -0.77 kg/m2(95%CI -0.84, -0.68).Height overestimation was greater in men (2.14 cm vs. 1.60 cm in women, p <0.001), and in both sexes was greater in the older age groups (p <0.001). The validity of weight estimation did not differ by sex or age group, however underestimation increased as body weight increased (mean differences in increasing weight quartiles were 0.08, -0.63, -0.59, -0.93 kg for males, and -0.18, -0.67, -0.49, -1.34 kg for females).In order to accurately assess the prevalence of obesity and the impact of weight management interventions in New Zealand, more research is needed on the agreement of self-reported and measured BMI. Since more recent national surveys have not included collection of both self-reported and measured data,23,24 this study uses data from the 1989/1990 Life in New Zealand Survey (LINZ)25 to examine the agreement between self-reported and measured height, weight and BMI, and between BMI categorisation based on self-reported and measured data.Given the significant limitation of the age of the dataset, analysis has been limited to one age group identified in many studies as being at particularly high risk of weight gain: 40-50 year olds.26-30Method Sample—The Life in New Zealand (LINZ) Survey was a nationwide cross-sectional health, nutrition, leisure and physical activity survey conducted in 1989/1990. The methods of this survey have been previously described.25 Adults (≥18 years) were recruited by stratified random sampling of the 1988 New Zealand electoral rolls, including the Māori rolls. In Phase I of the survey (April 1989 to March 1990), self-reported data such as age, sex, height, weight, ethnicity, occupation and SES were gathered by postal questionnaires. Participants were unaware at the time of questionnaire completion that height and weight would subsequently be measured. In Phase II, participants from 20 electorates considered to be representative of the country (in terms of urban-rural composition) were selected for health checks. Health checks were conducted between June and August 1989 and included detailed anthropometric measurements. Participant height without shoes was measured to the nearest millimetre using a calibrated stadiometer. Weight without shoes or heavy clothing was measured to the nearest 0.1 kg. A correction factor of 0.5 kg was subtracted from measured weights to take into account the light clothing worn by participants. BMI was calculated for each participant from measured height and weight. Data analysis—Measured BMI values were used to classify participants as underweight (<18.5 kg/m2) normal weight (18.5-24.99 kg/m2), overweight (25-29.99 kg/m2) and obese (≥30 kg/m2) according to the World Health Organization criteria.31 SES was measured on a 6-point scale (1=highest, 6=lowest) using self-reported information on employment, qualifications and household income.25 SES categories 1 and 2, and 4 to 6 were collapsed to produce three SES categories. Participants could indicate identification with more than one ethnic group and were assigned to one of five ethnicity categories prioritized as follows: New Zealand Māori, Cook Island Māori, Samoan, ‘Other', and finally New Zealand European. The classification of ethnicity in the present study is different to that in the original LINZ analyses, where New Zealand Māori was prioritized and all other participants classified as ‘Other New Zealanders'.32 Statistical analysis—Difference scores for height, weight and BMI were calculated by subtracting measured values from self-reported values. Means for self-reported and measured values were compared using paired sample t-tests. Difference scores for BMI were plotted against the mean of self-reported and measured values in a Bland Altman plot.33 Limits of agreement were calculated as mean difference ± 1.96 standard deviations of the difference. BMI categories based on self-reported and measured data were cross-tabulated, and linear weighted kappa statistics calculated to determine degree of concordance. Multiple linear regression analysis was used to evaluate whether age, sex, ethnicity, SES and measured BMI category were independently associated with the difference between measured and self-reported BMI. All analyses were undertaken using Stata software (version 12).34 Results Response rates to the LINZ survey were approximately 80% for Phase I questionnaires and 56% for Phase II health checks, after taking into account participants who were deceased or away from address at the time of recruitment.32 Phase II response rates were significantly lower in individuals from the Māori electoral rolls (35.5%) than from the General rolls (58.3%).32 Age specific response rates were not available. A total of 346 40-50 year old participants provided both self-reported and measured height and weight. One woman who overestimated weight by 30 kg was excluded as data checking revealed a probable transposition error. The ethnicity and socio-economic status of the sample is displayed in Table 1. Mean (SD) age of participants was 44.1 (3.1) years and 51% of the sample was male. Table 1. Participant ethnicity and Socio-Economic Status of 40-50 year olds in the 1989 LINZ survey (n=345) Characteristic n (%) Ethnicitya NZ European 322 (93.33) NZ Māori 17 (4.93) Other 6 (1.74) Socioeconomic Status b 1-2 114 (34.44) 3 106 (32.02) 4-6 111 (33.53) a Participants could indicate identification with more than one ethnic group and were assigned to one of five ethnicity categories prioritised as follows: New Zealand Māori, Cook Island Māori, Samoan, ‘Other', and finally New Zealand European.32 b SES measured on a 6-point scale (1=highest, 6=lowest) using self-reported information on employment, qualifications and household income.25 Data on SES were not available for 14 participants. Mean differences between self-reported and measured height, weight and BMI for men and women are displayed in Table 2. Self-reported weight was not significantly different from measured weight in men (p=0.905) or women (p=0.129). Height was significantly overestimated in both sexes (men 1.08 cm p<0.001, women 0.61 cm p<0.001), resulting in a small, statistically significant underestimation of BMI in men (-0.31 kg/m² p<0.001) and women (-0.26 kg/m² p<0.001). Table 2. Comparison of measured and self-reported height, weight, and derived body mass index in middle-aged men and women Characteristic Self-reported Mean (SD) Measured Mean (SD) Mean difference (95% CI) Minimum, maximum differences P value for difference Men (n=177) Height (cm) 176.57 (6.50) 175.48 (6.03) 1.08 (0.58, 1.59) -18.50, 21.1 <0.001* Weight (kg) 82.75 (12.06) 82.74 (12.22) 0.02 (-0.24, 0.27) -6.20, 4.20 0.905 BMI (kg/m2) 26.59 (4.01) 26.90 (4.05) -0.31 (-0.48, -0.14) -5.82, 5.77 <0.001* Women (n=168) Height (cm) 163.56 (5.51) 162.95 (4.92) 0.61 (0.35, 0.87) -5.00, 6.50 <0.001* Weight (kg) 69.19 (14.62) 69.41 (14.92) -0.22 (-0.49, 0.06) -9.80, 10.1 0.129 BMI (kg/m2) 25.90 (5.48) 26.16 (5.58) -0.26 (-0.41, -0.11) -4.67, 4.23 <0.001* BMI categories defined as: underweight <18.5; normal weight 18.5-24.99; overweight 25.0-29.99; obese ≥30.031 *Statistically significant difference, paired t-test Note: Mean difference calculated as self-reported-measured data (positive values therefore indicate overestimation) Figure 1 is a Bland Altman plot33 showing the extent of agreement between measured and self-reported BMI values for sample participants (male and female data combined). Figure 1. Bland Altman plot of the difference between self-reported and measured BMI vs. the mean of self-reported and measured BMI (male and female data combined). The solid line represents the mean difference (-0.29 kg/m²) and the dashed lines represent 95% limits of agreement (-2.40 kg/m² and 1.83 kg/m²). A comparison of classification into BMI categories based on self-reported and measured BMI is shown in Table 3. Overall, 85.3% of men and 92.9% of women were correctly classified into BMI category using self-reported data (linear weighted kappa 0.80 and 0.93 respectively). Table 3. Comparison of classification into body mass index (BMI) categories using measured and self-reported data (n=345) Self-reported BMI (kg/m2) Measured BMI (kg/m2) Total <18.5 18.5-24.9 25-29.9 ≥30.0 Men (n=177) <18.5 0 0 0

Summary

Abstract

Aim

To examine the agreement between self-reported and measured height, weight and BMI in 40-50 year old New Zealand men and women.

Method

Self-reported and measured height, weight and derived BMI were examined using data from 345 40-50 year old participants in the 1989/1990 Life In New Zealand Survey. Factors associated with biased reporting were assessed using regression models.

Results

Height was overestimated by men (1.08 cm, 95%CI 0.58, 1.59 p

Conclusion

Self-reported height and weight from New Zealand 40-50 year olds in 1989 produced BMI estimates valid for use in epidemiological studies, especially when used as a continuous variable. Our analyses need to be replicated using data from a current and representative New Zealand sample.

Author Information

Heidi Sharples, MSc student, Department of Human Nutrition; Peter Crutchley, MSc student, Department of Human Nutrition; Jos 00e9 A Garc 00eda, Lecturer, Department of Preventive & Social Medicine; Andrew Gray, Research Fellow (Biostatistician), Department of Preventive & Social Medicine; Caroline C Horwath, Senior Lecturer, Department of Human Nutrition; University of Otago, Dunedin

Acknowledgements

We thank Professor David Russell, Dr Noela Wilson, Professor Peter Herbison and Associate Professor Winsome Parnell for collecting the Life In New Zealand Survey data used in this study as well as Allison Gabucan, Marcus Dafu Du and Emily Watson (University of Otago) for assistance with data analysis.

Correspondence

Dr Caroline Horwath, Department of Human Nutrition, University of Otago, PO Box 56, Dunedin, New Zealand. Fax: + 64 (03) 4797958

Correspondence Email

caroline.horwath@otago.ac.nz

Competing Interests

None.

Kelly T, Yang W, Chen CS, et al. Global burden of obesity in 2005 and projections to 2030. Int J Obes. 2008;32(9):1431-7.Ministry of Health and University of Auckland. Nutrition and the burden of disease: New Zealand 1997-2011. Wellington: Ministry of Health; 2003.Flegal KM, Graubard BI, Williamson DF, Gail MH. Excess deaths associated with underweight, overweight, and obesity. JAMA. 2005;293(15):1861-7.Gibson RS. Principles of Nutritional Assessment. 2nd ed. Oxford: Oxford University Press; 2005, p259-64.Song X, Pitkaniemi J, Gao W, et al. Relationship between body mass index and mortality among Europeans. Eur J Clin Nutr. 2012;66(2):156-165.Zheng W, McLerran DF, Rolland B, et al. Association between body-mass index and risk of death in more than 1 million Asians. N Engl J Med. 2011;364(8):719-729.Taylor RW, Brooking L, Williams SM, et al. Body mass index and waist circumference cutoffs to define obesity in indigenous New Zealanders. Am J Clin Nutr. 2010;92(2):390-397.Bell AC, Swinburn BA, Simmons D, et al. Heart disease and diabetes risk factors in Pacific Islands communities and associations with measures of body fat. N Z Med J. 2001;114(1131):208-213.Turley M, Tobias M, Paul, S. Non-fatal disease burden associated with excess body mass index and waist circumference in New Zealand adults. Aust NZ J Public Health. 2006;30(3):231-237.Huxley RS, Mendis S, Zheleznyakov E, et al. Body mass index, waist circumference and waist:hip ratio as predictors of cardiovascular risk - a review of the literature. Eur J Clin Nutr. 2010;64(1):16-22.Bouchard C. BMI, fat mass, abdominal adiposity and visceral fat: where is the 'beef'? Int J Obes (Lond). 2007;31(10):1552-1553Gelber RP, Gaziano JM, Orav EJ, et al. Measures of obesity and cardiovascular risk among men and women. J Am Coll Cardiol. 2008;52(8):605-615.Stommel M, Schoenborn CA. Accuracy and usefulness of BMI measures based on self-reported weight and height: findings from the NHANES & NHIS 2001-2006. BMC Public Health. 2009;9:421-31.Rothman KJ. BMI-related errors in the measurement of obesity. Int J Obes. 2008; 32:S56-S59.Gorber S, Tremblay M, Moher D, Gorber B. A comparison of direct vs. self report measures for assessing height weight and body mass index: a systematic review. Obes Rev. 2007;8:307-26.Gillum RF, Sempos CT. Ethnic variation in validity of classification of overweight and obesity using self-reported weight and height in American women and men: the Third National Health and Nutrition Examination Survey. BMC Nutr J. 2005;4:27.Spencer EA, Appleby PN, Davey GK, Key TJ. Validity of self-reported height and weight in 4808 EPIC-Oxford participants. Public Health Nutr. 2002;5(4):561-5.Burton N, Brown W, Dobson A. Accuracy of body mass index estimated from self-reported height and weight in mid-aged Australian women. Aust NZ J Public Health. 2010;34(6):620-3.Wada K, Tamakoshi K, Tsunekawa T, et al. Validity of self-reported height and weight in a Japanese workplace population. Int J Obes (Lond). 2005;29(9):1093-9.Dekkers JC, van Wier MF, Hendriksen IJM, et al. Accuracy of self-reported body weight, height and waist circumference in a Dutch overweight working population. BMC Med Res Methodol. 2008;8:69.Stewart AW, Jackson RT, Ford MA, Beaglehole R. Underestimation of relative weight by use of self-reported height and weight. Am J Epidemiol. 1987;125(1):122-6.Craig BM, Adams AK. Accuracy of body mass index categories based on self-reported height and weight among women in the United States. Matern Child Health J. 2008;13(4):489-96.Parnell WR, Wilson NC, Russell DG. Methodology of the 1997 New Zealand National Nutrition Survey. NZ Med J. 2001;114(1128):123-6.University of Otago and Ministry of Health. Methodology Report for the 2008/09 New Zealand Adult Nutrition Survey. Wellington: Ministry of Health; 2011.Russell DG, Wilson NC. Life in New Zealand Commission Report Volume I: Executive Overview. Dunedin: University of Otago; 1991.Ball K, Crawford D, Ireland P, et al. Patterns and demographic predictors of 5-year weight change in a multi-ethnic cohort of men and women in Australia. Public Health Nutr. 2003;6(3):269-280.Sternfeld B, Wang H, Quesenberry CP, JR et al. Physical activity and changes in weight and waist circumference in midlife women: findings from the Study of Womens Health Across the Nation. Am J Epidemiol. 2004;160(9):912-22.Williams LT, Young AF, Brown WJ. Weight gained in two years by a population of mid-aged women: How much is too much? Int J Obes. 2006;30(8):1229-1233.Nafziger AN, Lindvall K, Norberg M, et al. Who is maintaining weight in a middle-aged population in Sweden? A longitudinal analysis over 10 years. BMC Public Health. 2007;7:108.Rissanen A, Heliovaara M, Aromaa A. Overweight and anthropometric changes in adulthood: a prospective study of 17,000 Finns. Int J Obes. 1988;12(5):391-401.World Health Organisation. Obesity: Preventing and Managing the Global Epidemic: Report on a WHO consultation. Technical Report Series No.854. Geneva: World Health Organization; 2000.Russell DG, Wilson NC, Spears G, Herbison P. Life in New Zealand Commission Report Volume II: Survey Protocol. Dunedin: University of Otago; 1991.Bland JM, Altman DG. Measuring agreement in method comparison studies. Stat Methods Med Res.1999;8(2):135-60.StataCorp. 2011. Stata Statistical Software: Release 12. College Station, TX: StataCorp LP.Landis JR, Koch G. The measurement of observer agreement for categorical data. Biometrics.1977;33:159-74.Katzmarzyk PT, Davis C. Thinness and body shape of Playboy centerfolds from 1978 to 1998. Int J Obes Relat Metab Disord. 2001;25(4):590-592.Leit RA, Pope HG Jr., Gray JJ. Cultural expectations of muscularity in men: the evolution of playgirl centerfolds. Int J Eat Disord. 2001;29(1):90-93.Andreyeva T, Puhl RM, Brownell KD. Changes in perceived weight discrimination among Americans, 1995-1996 through 2004-2006. Obesity (Silver Spring). 2008; 16(5):1129-1134.Stommel M, Osier N. Temporal changes in bias of body mass index scores based on self-reported height and weight. Int J Obes (Lond). 2012. Epub 02/05/2012Department of Statistics. New Zealand Census of population and dwellings 1986.Total population statistics. Wellington: Department of Statistics; 1987.

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