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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.14236 |
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| _version_ | 1866915500272910336 |
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| author | Phillips, Harriette Price, Aiden Mengersen, Kerrie |
| author_facet | Phillips, Harriette Price, Aiden Mengersen, Kerrie |
| contents | Using Australian children as a case study, this paper aims to develop vulnerability indices to characterise the health and well-being of children aged 0-5 years old. The indices are used to identify differences in children's health and well-being across geographic regions and identify clusters of regions with similar characteristics. The approach is underpinned by two well-known statistical methods, namely Principal Component Analysis and K-Means Clustering. The identification of these regions with similar vulnerability characteristics can then be used to derive new insights into drivers of children's health and well-being and support improved decision-making for services in Australia. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_14236 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Geographic Characterisation of Children's Health and Wellbeing through Vulnerability Indices Using Principal Component Analysis (PCA) and K-Means Clustering Phillips, Harriette Price, Aiden Mengersen, Kerrie General Mathematics Using Australian children as a case study, this paper aims to develop vulnerability indices to characterise the health and well-being of children aged 0-5 years old. The indices are used to identify differences in children's health and well-being across geographic regions and identify clusters of regions with similar characteristics. The approach is underpinned by two well-known statistical methods, namely Principal Component Analysis and K-Means Clustering. The identification of these regions with similar vulnerability characteristics can then be used to derive new insights into drivers of children's health and well-being and support improved decision-making for services in Australia. |
| title | Geographic Characterisation of Children's Health and Wellbeing through Vulnerability Indices Using Principal Component Analysis (PCA) and K-Means Clustering |
| topic | General Mathematics |
| url | https://arxiv.org/abs/2509.14236 |