BMI is often a go-to health measurement tool.
Body Mass Index (BMI) uses height and weight measurements to classify a person as ‘underweight’, ‘healthy weight’, ‘overweight’ or ‘obese’. BMI is calculated by dividing weight (kg) by height (m) squared.
For example, a woman 1.7m tall weighing 65kg has a BMI of 22.5
Click here to use the Ministry of Health’s BMI calculator, however, we recommend you keep reading further to learn about the limitations of BMI.
A BMI in the healthy weight range is associated with the lowest risk of disease. These BMI ranges apply to all ethnic groups, as the New Zealand Ministry of Health follows the World Health Organisation’s recommendation not to use specific ethnic BMI ranges.
Note: BMI should be used as a guide only and is not appropriate
BMI was initially developed as a tool to quickly measure weight status at a population level. Many people criticize the fact that it has been used as a measure of individual health.
BMI does not differentiate between muscle and fat, for example, someone who is muscular might sit at a higher BMI and be classified as overweight or obese even though they might be a low-fat mass and would be considered generally healthy. BMI also does not account for where the fat is stored. Research has shown us that fat stored around your abdomen (around your waist) is associated with a higher disease risk (Sun et al., 2019).
The association between BMI and disease risk is not consistent across all ethnicities. For example, Asian ethnicities compared with non-Asians have a higher risk of heart disease with a lower BMI because they are predisposed to store more fat around their middle.
BMI can be stigmatising. Research has found that when a doctor or health care professional only focuses on BMI or weight (Phelan et al., 2015), patients may feel stigmatised and may not receive the care they need.
Despite all the criticisms of BMI, a large meta-analysis (where several studies have been grouped together) found that a person’s risk of chronic disease and early death does indeed increase with a BMI lower than 18.5 (“underweight”) or of 25 or greater (“overweight”) and 30.0 or greater (“obese”) (Aune et al., 2016). In a time-bound setting like a GP clinic, it can be used as a quick screening tool if relevant. However, it is clear it should be not used as the sole measure for health status and users should be aware of its flaws.
Blood test results, fitness levels, diet quality, energy levels, sleep quality, and mental well-being are more important measures of health.
Like BMI, waist circumference is easy and inexpensive to measure, but compared to BMI, stronger evidence suggests that waist circumference measurement is better at determining whether your weight is affecting your health. This is because waist circumference takes into account the fat stored around your waist which has a strong association with metabolic diseases such as type 2 diabetes and heart disease. If your waist measurement is greater than those listed below you are at increased risk of cardiovascular disease and developing type 2 diabetes. These guidelines have been set by the World Health Organisation.
However, there are still limitations. Some evidence suggests that lower cut-offs may be more appropriate for Asian adults (Wildman et al., 2004). This is because at the same waist circumference people of Asian ethnicity have a higher risk of metabolic disease compared to non-Asian people.
Another, more tailored guide is the waist-to-height ratio: this states that men and women should strive to keep their waist circumference to no more than half their height.
If you have concerns about your BMI or waist circumference, please discuss these with your doctor or a registered dietitian. Similar to BMI, waist circumference is just one measure of health and taking into other factors mentioned above (blood test results, fitness levels etc.) still remain important.
Aune, D., Sen, A., Prasad, M., Norat, T., Janszky, I., Tonstad, S., Romundstad, P., & Vatten, L. J. (2016). BMI and all cause mortality: systematic review and non-linear dose-response meta-analysis of 230 cohort studies with 3.74 million deaths among 30.3 million participants. BMJ (Clinical research ed.), 353, i2156. https://doi.org/10.1136/bmj.i2156
Phelan, S. M., Burgess, D. J., Yeazel, M. W., Hellerstedt, W. L., Griffin, J. M., & van Ryn, M. (2015). Impact of weight bias and stigma on quality of care and outcomes for patients with obesity. Obesity reviews : an official journal of the International Association for the Study of Obesity, 16(4), 319–326. https://doi.org/10.1111/obr.12266
Sun, Y., Liu, B., Snetselaar, L. G., Wallace, R. B., Caan, B. J., Rohan, T. E., Neuhouser, M. L., Shadyab, A. H., Chlebowski, R. T., Manson, J. E., & Bao, W. (2019). Association of Normal-Weight Central Obesity With All-Cause and Cause-Specific Mortality Among Postmenopausal Women. JAMA network open, 2(7), e197337. https://doi.org/10.1001/jamanetworkopen.2019.7337
Wildman, R. P., Gu, D., Reynolds, K., Duan, X., & He, J. (2004). Appropriate body mass index and waist circumference cutoffs for categorization of overweight and central adiposity among Chinese adults. The American journal of clinical nutrition, 80(5), 1129–1136. https://doi.org/10.1093/ajcn/80.5.1129
Last reviewed: 20/06/2022
Last modified: June 20, 2022
