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Effects of health and social care spending constraints on mortality in England: a time trend analysis
  1. Johnathan Watkins1,2,
  2. Wahyu Wulaningsih2,3,
  3. Charlie Da Zhou4,
  4. Dominic C Marshall5,
  5. Guia D C Sylianteng2,6,
  6. Phyllis G Dela Rosa2,7,
  7. Viveka A Miguel2,8,
  8. Rosalind Raine9,
  9. Lawrence P King10,
  10. Mahiben Maruthappu9
  1. 1 Institute for Mathematical and Molecular Biomedicine, King’s College London, London, UK
  2. 2 PILAR Research and Education, Cambridge, UK
  3. 3 MRC Unit for Lifelong Health and Ageing, University College London, London, UK
  4. 4 Medical Sciences Division, University of Oxford, Oxford, UK
  5. 5 Oxford University Clinical Academic Graduate School, John Radcliffe Hospital, Oxford, UK
  6. 6 London School of Hygiene and Tropical Medicine, London, UK
  7. 7 University of the Philippines Manila, Manila, Philippines
  8. 8 University of the Philippines Diliman, Quezon City, Philippines
  9. 9 Department of Applied Health Research, University College London, London, UK
  10. 10 Department of Sociology, University of Cambridge, Cambridge, UK
  1. Correspondence to Dr Mahiben Maruthappu; m.maruthappu{at} and Dr Johnathan Watkins; jwatkins{at}


Objective Since 2010, England has experienced relative constraints in public expenditure on healthcare (PEH) and social care (PES). We sought to determine whether these constraints have affected mortality rates.

Methods We collected data on health and social care resources and finances for England from 2001 to 2014. Time trend analyses were conducted to compare the actual mortality rates in 2011–2014 with the counterfactual rates expected based on trends before spending constraints. Fixed-effects regression analyses were conducted using annual data on PES and PEH with mortality as the outcome, with further adjustments for macroeconomic factors and resources. Analyses were stratified by age group, place of death and lower-tier local authority (n=325). Mortality rates to 2020 were projected based on recent trends.

Results Spending constraints between 2010 and 2014 were associated with an estimated 45 368 (95% CI 34 530 to 56 206) higher than expected number of deaths compared with pre-2010 trends. Deaths in those aged ≥60 and in care homes accounted for the majority. PES was more strongly linked with care home and home mortality than PEH, with each £10 per capita decline in real PES associated with an increase of 5.10 (3.65–6.54) (p<0.001) care home deaths per 100 000. These associations persisted in lag analyses and after adjustment for macroeconomic factors. Furthermore, we found that changes in real PES per capita may be linked to mortality mostly via changes in nurse numbers. Projections to 2020 based on 2009-2014 trend was cumulatively linked to an estimated 152 141 (95% CI 134 597 and 169 685) additional deaths.

Conclusions Spending constraints, especially PES, are associated with a substantial mortality gap. We suggest that spending should be targeted on improving care delivered in care homes and at home; and maintaining or increasing nurse numbers.

  • health care
  • social care
  • spending
  • expenditure
  • mortality
  • PYLL
  • life expectancy
  • time trend

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  • JW and WW contributed equally.

  • Contributors JW and MM conceived and designed the study. JW, WW, CDZ, DM and MM obtained the data. JW, WW, GDCS, PGDR and VAM conducted data formatting. JW and WW carried out statistical analysis with input from LPK. All authors helped interpret the findings. JW, WW and MM wrote the first draft of the manuscript with input from DCM, CDZ, RR and LPK. All authors provided input to subsequent drafts. All authors had full access to all of the data in the study and can take responsibility for its integrity and the accuracy of the data analysis.

  • Funding No funding was received for this study. WW is employed under Medical Research Council grant MC_UU_12019/2 and MC_UU_12019/4.

  • Competing interests MM is a co-founder of Cera, a technology-enabled homecare provider.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement All data are in the public domain.

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