Subjective wellbeing at different spatial scales for individuals satisfied and dissatisfied with life.

Ida Kubiszewski,Nabeeh Zakariyya,Diane Jarvis

doi:10.7717/peerj.6502

Ida Kubiszewski, Nabeeh Zakariyya + Show 1 more

Open Access

https://doi.org/10.7717/peerj.6502

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Journal: PeerJ	Publication Date: Feb 21, 2019
Citations: 11	License type: CC BY 4.0

Affiliation: Australian National University, James Cook University

Abstract

Indicators that attempt to gauge wellbeing have been created and used at multiple spatial scales around the world. The most commonly used indicators are at the national level to enable international comparisons. When analyzing subjective life satisfaction (LS), an aspect of wellbeing, at multiple spatial scales in Australia, variables (drawn from environmental, social, and economic domains) that are significantly correlated to LS at smaller scales become less significant at larger sub-national scales. The reverse is seen for other variables, which become more significant at larger scales. Regression analysis over multiple scales on three groups (1) all individuals within the sample, (2) individuals with self-reported LS as dissatisfied (LS ≤ 5), and (3) individuals self-reporting LS as satisfied (LS > 5), show that variables critical for LS differ between subgroups of the sample as well as by spatial scale. Wellbeing measures need to be created at multiple scales appropriate to the purpose of the indicator. Concurrently, policies need to address the factors that are important to wellbeing at those respective scales, segments, and values of the population.

Highlights

Over the past few decades, dozens of wellbeing indicators have been developed as a means of tracking societal progress, comparing countries, or developing policies (Smith et al, 2013)
Descriptive statistics To understand the relationships between objective variables and average life satisfaction (LS) at different spatial scales, it is important to examine how the aggregation of these objective variables differs across the spatial scales
At Statistical Area Level 1 (SA1), the average LS is 7.81 with a standard deviation of ±1.24 between the SA1 scales, compared to the standard deviation of LS within an SA1 area, which is ±0.69. This implies that at the SA1 level, individual LS scores between areas are more dispersed than the aggregated scores within an area

Summary

Introduction

Over the past few decades, dozens of wellbeing indicators have been developed as a means of tracking societal progress, comparing countries, or developing policies (Smith et al, 2013). These indicators are frequently multi-faceted, reflecting the influence of environmental, social, and economic factors on wellbeing. Many of these indicators aggregate variables, either objective or subjective, to determine an overall wellbeing of a population. Most indicators are created to measure average wellbeing at a national level, while a few focus on a single small community.

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