Measuring the stress of moving house

Moving is considered stressful, but just how stressful is it? Dr William Cheung set out to answer this question and, in doing so, developed an original method of investigation.

Man sitting among packing boxes as he moves house.
A recent study suggests that individuals dealing with high stress levels are predisposed to move house.

University of Auckland Business School researcher Dr William Cheung is analysing micro-level data about people and households to examine the effects of moving house on mental well-being and stress.

His study, co-authored with business analyst Daniel Wong and published in open-access journal Urban Science, scrutinises stress levels among adults in the Auckland region, namely homeowners and renters, alongside a control group of non-movers.

Overall, the results show that the average stress level of homeowners is significantly higher than renters, and those who move more frequently are more stressed than those who don't. The data also suggests that individuals dealing with high stress levels are predisposed to move house.

While acute stresses seem to result in one-off movements, Dr Cheung says chronic stresses result in more frequent movement. The study also shows that stress levels decrease over time when individuals don't move.

Cheung says social housing tenants have much higher baseline stress levels than both homeowners and renters.

Dr William Cheung.
Dr William Cheung, a senior lecturer in property at the Business School, was awarded a 2022 early-career research excellence medal to recognise his outstanding contribution to research.

"While research has shown that moving house is detrimental to mental well-being," Dr Cheung says in his paper, "our studies further suggest that frequent relocation and the housing tenure types, especially owner-occupier, is a substantial contributor to stress."

As a result, the study's authors recommend implementing housing strategies that ensure housing can be sustained over time. Dr Cheung says this may include assistance programmes that make housing more attainable for the vulnerable, such as those encountering mental illness.

"We need economic programmes that aid individuals at risk of losing their homes and, as well as providing stable housing, mental health services must be available, easily accessible among urban residents, and designed to remain amenable under transient circumstances."

The average stress levels of non-movers, renters, homeowners, and social housing residents aged between 19 and 54 living in urban Auckland between 2013 and 2018 were analysed by Cheung and Wong using the government's Integrated Data Infrastructure, which is based on micro-level individual census data.

This census data enabled them to reconstruct what's known as the Social Readjustment Rating Scale (SRRS), a stress comparison scale developed in the 1960s by two psychiatrists.

The original SRRS attributes up to 100 points to different life stressors, ranging from 100 points for a spouse's death to 11 points for minor law violations. Other examples include moving house (20 points), incurring a large mortgage (37) and divorce (73 points).

Dr Cheung says the new method resulted in an instrument that can measure the socioeconomic impact on an individual in any population segment far more cost-effectively than current measures.

Using the census data and the SRRS model also proved more efficient than conventional surveys, with better sensitivity and an increased ability to identify influences on the individual.

"We advanced our understanding of the stress of moving homes; the influence of mobility on place experience; and the circumstances, advantages and challenges of moving home over a resident's lifetime."

By progressing people's understanding of such stressors, Dr Cheung says researchers can contribute to broader discussions on how an individual's personal history and social mobility influence their social well-being.

Full paper:

Cheung, K.S. & Wong, D. (2022). Measuring the Stress of Moving Homes: Evidence from the New Zealand Integrated Data Infrastructure. Urban Science, 6(4), 75. https://doi.org/10.3390/urbansci6040075

 

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