A recent study published in Economics & Human Biology suggests that carrying excess body weight does not inherently reduce a person’s chances of finding employment in Australia. By analyzing long-term data, researchers found no consistent evidence that overweight or obese individuals face widespread hiring discrimination. The findings suggest that when past employment history is considered, body mass has little to no impact on current job prospects.

Obesity rates have increased significantly across the globe over the past few decades. In Australia alone, roughly one in three adults were classified as obese in 2022. This rise in body mass presents various health risks, but it also raises questions about potential social and economic consequences.

“The international literature generally finds that excess body mass is associated with poorer labour market outcomes, particularly lower employment probabilities for women, with growing evidence that these effects reflect discrimination and stigma rather than productivity alone,” said researcher Pundarik Mukhopadhaya, a professor of economics at Macquarie Business School. “The motivation of this research came from the growing prevalence of excess body mass in Australia and the relative lack of causal evidence on how it affects labour market outcomes,” he explained.

Mukhopadhaya supervised the research alongside Chris Heaton, which was led by former doctoral student Anushiya Vijayasivajie. Australia has anti-discrimination laws designed to protect workers, making it important to evaluate whether taste-based discrimination still negatively impacts hiring decisions. Taste-based discrimination happens when employers allow personal prejudices to influence their professional choices.

To conduct the investigation, the researchers utilized data from the Household, Income and Labour Dynamics in Australia survey. This large national project tracks the economic and personal well-being of thousands of Australian households over many years. The scientists focused on data collected between 2006 and 2019, intentionally stopping just before the pandemic to avoid unusual employment disruptions.

The final analysis included up to 10,233 unique individuals between the ages of 25 and 54. This resulted in a total of 76,307 separate survey observations over the thirteen-year tracking period. The researchers excluded full-time students and pregnant women to ensure the data accurately reflected the general working population.

To measure body mass, the scientists calculated each participant’s Body Mass Index. This standard measurement uses a person’s height and weight to estimate their total body fat. Participants were grouped into classifications based on guidelines from the World Health Organization, ranging from underweight to severely obese.

The researchers recorded whether each individual was employed or unemployed during each survey year. They also controlled for an extensive range of personal characteristics to ensure they were isolating the specific effect of body mass. These background factors included geographic location, education level, and early life experiences, such as the socioeconomic status of a person’s parents.

The researchers even included measures of personality, like a person’s willingness to take risks or their preference for immediate rewards over future benefits. Factoring in these elements helped the scientists paint a highly detailed picture of each individual. It also minimized the chance that other personal traits were secretly driving the employment outcomes.

To analyze this massive dataset, the scientists used two different mathematical approaches. The initial approach functions by assuming that unmeasured personal traits behave in a predictable, linear way. It also assumes that a person’s body mass operates independently, acting solely as a cause rather than an effect of their job status.

Under these specific conditions, the preliminary model suggested that individuals with higher body mass were slightly less likely to be employed. However, the researchers recognized that human lives rarely follow such strict, independent rules. For instance, being unemployed can lead to financial strain, which might force a person to rely on cheaper, heavily processed foods.

In this scenario, losing a job actually causes the weight gain, creating a loop known as reverse causality. To address this issue, the scientists applied a more advanced statistical technique known as the generalized method of moments. This preferred method relaxed the strict mathematical rules and accounted for the possibility that unemployment could lead to weight gain.

This advanced method also explicitly stripped away hidden, unchanging factors that might skew the results. When applying this more nuanced approach, the researchers found no statistical association between excess body mass and employment. This result held true across the entire sample and remained consistent regardless of whether self-employed workers were included.

“The results were sensitive to assumptions made for instance, accounting for individuals’ employment history yields results that differ substantively from results that do not account for individuals’ employment history,” Mukhopadhaya noted. When the data was split by gender, the researchers still found no evidence that heavier men or women were less likely to be employed in Australia.

The scientists also explored the idea of health-related productivity. They wondered if underlying physical or mental health conditions might cause heavier individuals to miss work or be perceived as less productive. By comparing statistical models, they found very weak evidence that health-related productivity influenced the relationship between body weight and employment.

While the study provides a detailed look at the Australian labor market, there are some potential limitations to consider. The findings highlight how sensitive economic research is to the specific mathematical models chosen. “The type of methodology used to investigate the relationship matters and as such, this should be kept in mind when interpreting/understanding the results,” Mukhopadhaya explained.

The study also relied on self-reported heights and weights, which can introduce subjectivity bias. People tend to underestimate their weight, which could slightly skew the body mass calculations. To address this, the scientists ran tests using correction equations to adjust for known reporting biases, and the adjusted results closely matched the original findings.

Despite the lack of statistical significance in the final models, the researchers caution against ignoring the issue entirely. “While there is less than convincing evidence of hiring discrimination against individuals due to their excess body mass status, the potential for this type of discrimination to exist in Australia cannot be ruled out,” Mukhopadhaya said.

Moving forward, the research team hopes to expand their investigation to see how body weight impacts other professional outcomes. “Subject to the availability of resources, we would like to examine the effects on occupational sorting, job stability and tenure, hours worked and contract type,” Mukhopadhaya said. “Moreover, we would like to analyse differential effects by occupation and industry.”

The scientists hope their work inspires broader global investigations. “We hope this research serves as an impetus for further research using a more comprehensive dataset across multiple OECD countries,” Mukhopadhaya added.

The study, “The impact of excess body mass on employment prospects in Australia,” was authored by Anushiya Vijayasivajie, Pundarik Mukhopadhaya, and Chris Heaton.