Child poverty in the UK is a significant concern, with estimates suggesting a substantial portion of children living in poverty. Families with children are disproportionately affected compared to childless families. The provision of unpaid care, particularly for children with disabilities, is a considerable factor contributing to family financial strain. Unpaid care can impact parents' ability to work, leading to reduced income and increased financial pressures. Existing research has explored the links between poverty and disability, and poverty and unpaid care, but the three-way relationship has not been thoroughly investigated, particularly within the UK context. This study aims to fill this gap by examining how child disability, unpaid care, and poverty interact within families in the UK, using both income-based and material deprivation measures of poverty.

The literature review explores various aspects of child poverty in the UK, including the debate around its measurement and the challenges posed by the repeal of the Child Poverty Act 2010. It highlights the differences between before-housing costs (BHC) and after-housing costs (AHC) income poverty measures, with AHC often considered a more accurate reflection of living standards. The review examines the complexities of defining and measuring child poverty, considering both income and material deprivation, and acknowledges instances where families prioritize children's needs over their own. It discusses the higher poverty rates observed in families with disabled children and the impact of disability on families' financial, social, and emotional well-being, encompassing both direct costs (medical expenses) and indirect costs (reduced work opportunities). The review also touches upon the sociodemographic factors associated with poverty, such as education level, employment status, ethnicity, and household structure. Existing studies show varying results, with some indicating that families with disabled children are more likely to experience hardship and financial strain, while others highlight the lack of significant effect of disability on poverty trajectories when controlling for sociodemographic factors. The crucial difference in the current study is the explicit inclusion of unpaid care as a mediating factor in the relationship between disability and poverty.

The study employs secondary data from the 2018/19 Family Resources Survey (FRS), a face-to-face survey conducted in Great Britain and Northern Ireland, supplemented with data from the Households Below Average Income (HBAI) dataset. The analytical sample consists of 5451 benefit units with dependent children. Three response variables are analyzed: before-housing costs (BHC) poverty, after-housing costs (AHC) poverty, and child material deprivation. The AHC measure is used as it accounts for housing costs and is generally considered a better indicator of disposable income and living standards. The 60% of the median income threshold is used to determine poverty status. Material deprivation is measured using a composite index based on 21 questions about affordability of goods and services. Families are classified as materially deprived if they cannot afford at least five to six of the items. The sample is divided into three groups: families with children without disabilities, families with children with disabilities who do not provide unpaid care, and families with children with disabilities who provide unpaid care. Explanatory variables include sociodemographic factors like education level, occupation, ethnicity, housing tenure, number of dependent children, number of adults with disabilities, employment status, and average general health. Missing data are imputed using multiple imputation. Logistic regression models are used to analyze the relationship between sociodemographic factors and poverty outcomes for each group, examining the direct effect of disability and unpaid care on poverty while controlling for other covariates. Generalized Variance Inflation Factor (GVIF) tests are used to assess multicollinearity among variables. The analysis is conducted using R.

Descriptive statistics reveal differences between the groups. Families with children with disabilities are more likely to be materially deprived, lone-parent families, and live in socially rented accommodation. While the rate of material deprivation is significantly higher in families with disabled children, the AHC poverty rate is slightly lower in this group compared to families without disabled children. This unexpected finding is explored further in the discussion section. Logistic regression analysis shows that having children without disabilities increases the odds of AHC poverty compared to having children with disabilities. This counterintuitive result is attributed to the inclusion of disability benefits in income calculations. When disability benefits are removed, the AHC poverty rates are higher than for families without disabilities, aligning more closely with material deprivation rates. Providing unpaid care is associated with lower odds of AHC poverty. This finding seems to contradict existing research that links unpaid care to reduced income and increased poverty risk and is discussed in detail in the discussion section. The analysis reveals that not owning a house substantially increases the odds of material deprivation for both groups. Among families with children without disabilities, those with elementary jobs have significantly higher odds of material deprivation than those with managerial positions. For families with disabled children, higher education is associated with lower odds of material deprivation, while being from a non-white ethnic background increases the odds of material deprivation. When comparing families with disabled children providing unpaid care to those not providing it, a statistically significant difference is only noted for material deprivation. Private renting increased the likelihood of material deprivation significantly more for those providing unpaid care compared to those who did not.

The findings highlight the complexities of the relationship between child disability, unpaid care, and poverty. The unexpected result that families with non-disabled children had higher odds of AHC poverty compared to those with disabled children is likely due to the inclusion of disability benefits in the income calculation. The inclusion of disability benefits in total income can artificially raise a family's income above the poverty line despite significant additional expenses linked to disability. The lower odds of AHC poverty among families providing unpaid care also contradict prior research. Potential explanations for this unexpected result include that families with higher incomes are more likely to provide unpaid care, and that the income-reducing effects of unpaid care might be offset by higher pre-existing income levels, although further investigation is necessary using longitudinal data. The significant effect of sociodemographic factors on material deprivation underscores the importance of addressing these factors to alleviate poverty and reduce inequality. Limitations in data, including potential bias in unpaid care reporting and the inability to disaggregate disability benefit types, are acknowledged.

This study provides valuable insights into the complex interplay between child disability, unpaid care, and poverty in the UK. While sociodemographic factors significantly influence material deprivation across different groups, the direct effects of child disability and unpaid care on AHC poverty revealed some surprising results that require further investigation using longitudinal data and potentially qualitative methods. Future research should focus on disentangling the impact of disability benefits, exploring the reasons for families choosing to provide unpaid care, and examining the differential effects of various sociodemographic factors on families' financial well-being. The findings highlight the need for targeted policy interventions to support families with disabled children, considering the multiple dimensions of poverty and the significant role of unpaid care.

The study acknowledges several limitations. The FRS response rate of 50%, although considered reasonable by the survey's standards, might introduce non-response bias, particularly as some who declined participation cited time constraints and caring responsibilities. The measurement of unpaid care relies on self-reporting and a pre-defined list of activities, which may not capture the full extent or nuances of caregiving experiences. The study's inability to disaggregate disability benefits into those for children versus those for adults, limits the precise assessment of financial resources. Moreover, treating disability as a binary variable limits the analysis of the varying costs and support needs associated with different types and severities of disabilities.