burns 41 (2015) 437–445

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Geographical analysis of socioeconomic factors in risk of domestic burn injury in London 2007–2013 Jacob S. Heng a,b, Joanne Atkins c, Olivia Clancy a,b, Masao Takata a,b, Ken W. Dunn d, Isabel Jones c, Marcela P. Vizcaychipi a,b,* a

Magill Department of Anaesthesia, Intensive Care and Pain Management, Chelsea and Westminster Hospital, London, United Kingdom b Imperial College Faculty of Medicine, London, United Kingdom c Plastic Surgery and Burns Service, Chelsea and Westminster Hospital, London, United Kingdom d Department of Burns and Plastic Surgery Regional Burns Service, University Hospital of South Manchester NHS Foundation Trust, Manchester, United Kingdom

article info

abstract

Article history:

Purpose: This study aims to explore the geographical distribution of burn injuries in Greater

Accepted 3 December 2014

London and the association of socioeconomic factors in areas at risk. Methods: Data on burn injury cases classified as occurring in patients’ own homes in Greater

Keywords:

London and admitted to a specialised burns service for 1 day during a 7-year period were

Domestic burn injury

obtained from the International Burn Injury Database (iBID). Age- and gender-adjusted

Geographical mapping

standardised incidence ratios (SIRs) were calculated for each Lower Layer Super Output Area

Spatial analysis

(LSOA) in Greater London. Bayesian methods were used to calculate relative risks as best

Bayesian

estimates of spatially-smoothed SIRs.

Socioeconomic

Results: Of a total of 2911 admissions to specialised burns services in Greater London in the study period, 2100 (72.1%) cases occurred in patients’ own homes. Percentage of ethnic minorities ( p = 0.005), Income Deprivation Affecting Children Index ( p < 0.001), Health Deprivation and Disability Score ( p = 0.031), percentage of families with 3 or more children ( p = 0.004) and Barriers to Housing and Services Score ( p = 0.001) remained independently associated with the relative risk of paediatric domestic burn injury in a multivariate linear regression model. Percentage of ethnic minorities ( p < 0.001), Health Deprivation and Disability Score ( p < 0.001) and Barriers to Housing and Services Score ( p = 0.036) remained independently associated with the relative risk of adult domestic burn injury in a multivariate linear regression model. Conclusions: Socioeconomic factors are associated with an increased risk of burn injury in Greater London, but may be more important in children than adults. The specific factors identified are ethnicity, poor general health, household structure, housing issues and income deprivation affecting children. # 2014 Elsevier Ltd and ISBI. All rights reserved.

* Corresponding author at: Chelsea & Westminster Hospital, Magill Department of Anaesthesia, Magill Department of Anaesthesia, 369 Fulham Road, London SW10 9NH, United Kingdom. Tel.: +44 208 746 8903; fax: +44 203 315 5109.. E-mail address: [email protected] (M.P. Vizcaychipi). Abbreviations: BYM, Besag, York and Mollie; iBID, International Burn Injury Database; IDACI, Income Deprivation Affecting Children Index; IMD, Index of Multiple Deprivation; LSOA, Lower Layer Super Output Area; NBCG, UK National Burn Care Group; SIR, standardised incidence ratios; UK.NBID, UK National Burn Injury Database; VIF, variance inflation factor; %BAME, percentage of Black, Asian and other Minority Ethnic Groups. http://dx.doi.org/10.1016/j.burns.2014.12.001 0305-4179/# 2014 Elsevier Ltd and ISBI. All rights reserved.

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1.

burns 41 (2015) 437–445

Introduction

Burn injuries represent a significant health burden in the United Kingdom. Every year, there are 18.1 burn injuries per 100,000 population resulting in hospitalisation [1]. Serious burn injuries leading to death, or hospitalisation for more than 72 h, occurred in 4.7 cases per 100,000 population annually, contributing to 5.4% of all serious traumatic injuries [1]. Burn injuries are associated with a significant risk of mortality [2], as well as significant physical, functional and psychiatric sequelae in survivors. The economic costs to the health service are also substantial, with the cost of short-term care for a hot drink scald estimated at £1850, and the cost of a major paediatric burn estimated at £63,157. Given the significant costs of burn injuries to the individual and society, the potential benefit of targeted community-based preventative strategies [3] is of crucial importance in preventing burns morbidity and mortality. The majority of burn injuries occur in the victims’ own homes [4]. Previous studies worldwide have identified significant geographic clustering of burn injuries [5–9], suggesting that there may be common characteristics in the resident communities that potentially pre-dispose them to burn injuries. Age [10], socioeconomic deprivation [7,9–12], ethnicity [10,12], education status [11–13], adult employment status[12], living environment [7], household structure such as lone parent households [14] and large family size [15], as well as pre-existing disabilities [16,17], have all been implicated in the incidence and risk of burn injuries. In the 2011 Census of the United Kingdom population, the Greater London metropolitan area is officially the most populous city in Europe, with a population of approximately 8 million [18]. There is evidence of widespread variation in unintentional injury rates across London attributable to socioeconomic factors [19–22]. However, there have not been any studies of population burn injury rates or risk in London. This study aims to explore the geographical distribution of burn injuries in Greater London and the association of socioeconomic factors in areas at risk.

2.

Methods

2.1.

Data collection

The International Burn Injury Database (iBID1), incorporating the UK National Burn Injury Database (UK.NBID2), was created in 2004 [4]. This was achieved with funding from the UK National Burn Care Group (NBCG3) following the UK National Burn Care Review in 2001, with the purpose of matching the demand for burn care across a range of ages, burn injury severity and geographical locations in England and Wales [4]. Following the creation of the iBID data collection system and its requisite infrastructure, the commencement of data collection in April 2005 required all

burn services in England and Wales to collect and submit a minimum set of data for all admissions, with permission for centralisation of anonymised data for analysis and consideration initially by the NBCG and then by the regional Burn Care Networks from 2007 onwards [4]. For the purposes of our study, anonymised data for patients from Greater London admitted to a specialised burns service for one day or more during the 7-year period between January 2007 and December 2013 were obtained from iBID. Data extracted included patient’s age, gender, area of residence defined by the Lower Layer Super Output Area (LSOA4), place of burn injury, percentage of total body surface area burned (%TBSA), and intensive care unit admission. Only cases with the place of burn injury classified as ‘‘Own Home’’ were used for analysis. The data request was approved by the UK National Network for Burn Care Informatics Group. Greater London is divided into 4765 Lower Layer Super Output Areas (LSOAs) for the purposes of population census and public administrative data collection between the 2001 and 2011 Censuses [18]. Each LSOA is considered the smallest geographical unit for population census, and contains a population of between 1000 to 2000 [18]. Population and socioeconomic data for each LSOA, compiled by the Greater London Authority Intelligence Unit from different sources listed below, were obtained from the Greater London Authority website (http:// data.london.gov.uk). The English Index of Multiple Deprivation published by the Department for Communities and Local Government in 2010 (IMD5 2010), provides a measure of socioeconomic deprivation [23]. The IMD is a standard measure used in England for socioeconomic deprivation, and is constructed from seven different domains of deprivation with the following weightage: (i) income—22.5%, (ii) employment— 22.5%, (iii) health and disability—13.5%, (iv) education, skills and training—13.5%, (v) barriers to housing and services—9.3%, (vi) crime—9.3%, (vii) living environment—9.3%. The IMD scores are ranked nationally, with the most deprived areas having the highest scores and ranks with the lowest numerical values. In addition to the domain of deprivation scores mentioned above, the Income Deprivation Affecting Children Index (IDACI6) was obtained from the IMD 2010 statistics as a measure of the extent to which income deprivation affects children. The IDACI is a measure of the proportion of children aged 0–15 years living in income-deprived families, which are defined as those in receipt of income support or families with an income below 60% of the national median (before housing costs) and receiving Child Tax Credit [23]. Demographic, household structure, employment and education data from the 2011 Census were obtained from the Office of National Statistics. Demographic data of interest included population age structure; population density as measured by number of persons per hectare; percentage of Black, Asian and other Minority Ethnic Groups (%BAME7); percentage of residents not born in the UK; percentage of households where no adults over 16 years of age has English as their main language. Data on 4

LSOA—Lower Layer Super Output Area. IMD—Index of Multiple Deprivation. 6 IDACI—Income Deprivation Affecting Children Index. 7 %BAME—percentage of Black, Asian and other Minority Ethnic Groups. 5

1 2 3

iBID—International Burn Injury Database. UK.NBID—UK National Burn Injury Database. NBCG—UK National Burn Care Group.

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burns 41 (2015) 437–445

Table 1 – Characteristics of domestic burn injury cases in London 2007–2013. Characteristic Median Age (years) (interquartile range) Gender Male Female Not recorded Median %TBSA (%) (interquartile range) Inhalation injury ICU admission

Overall (n = 2100) 17 (1–47)

Calculation of standardised incidence ratios (SIRs)

Indirect standardisation by age and gender was employed. Patients were categorised into 5-year age groups from 0 to 4 years up to >90 years for each gender to give gender-age groups (e.g. males 0–4 years, females 0–4 years etc.). The corresponding population count for the whole of Greater London for each gender-age group was obtained from the 2011 Census. Expected rates for each gender-age group for each LSOA was calculated by multiplying the case rate (number of cases per 100,000 population) for each gender-age group for the whole of Greater London with the corresponding population count in each gender-age group for each LSOA. The expected number of cases for each LSOA was calculated by the summation of expected rates for all gender-age groups in the LSOA. Standardised incidence ratio (SIR8) for each LSOA was calculated by dividing the observed number of cases by the expected number of cases for each LSOA as detailed above. For the purposes of our analysis, paediatric (0–14 years) and adult (15 years) SIRs were calculated.

2.3.

Statistical analysis

Statistical analyses were carried out using R 3.1.0 for Max OS X (The R Foundation for Statistical Computing, 2013) and SPSS version 21.0 for Mac OS X (IBM Corp, 2012). Statistical smoothing was carried out using the widelyaccepted Besag, York and Mollie model (BYM9)[24] as low frequencies and small populations may produce unstable area-based estimates in disease mapping. The BYM model utilises Bayesian methods to analyse variation in admission rates in contiguous LSOAs (i.e. spatial variation) and across the entire city (i.e. non-spatial variation) to produce a posterior distribution of the expected relative risk of burns unit admission as an estimate of the smoothed standardised incidence ratio. The model was fitted using the R package CARBayes [25]. The mean of the posterior distribution of the expected relative risk was taken as the best estimate of the smoothed standardised incidence ratio (SIR) and used as the ‘relative risk’ in our analyses. 8 9

SIR—Standardised incidence ratios. BYM—Besag, York and Mollie.

1 (1–2)

1157 929 14 4.0 (2.0–7.0) 33 57

household structure included percentage of lone parent households and percentage of families with 3 or more children. Employment and education data of interest included percentage of working age adults who are unemployed, and percentage of working age adults with no qualifications.

2.2.

Paediatric (n = 1028)

591 430 7 5.0 (2.0–8.0) 2 23

Adult (n = 1071) 46 (33–66) 565 499 7 3.0 (1.0–7.0) 31 34

The relative risks of burn injury for children and adults were separately plotted against population parameters at the LSOA level to assess for any univariate correlation. Transformation was applied to any potential non-linear correlation to achieve linearity. The variables included IMD 2010 domains of deprivation scores, number of persons per hectare, %BAME, % of residents not born in the UK, % of households where no adults >16 years of age has English as their main language, % of unemployed adults and % of working age adults with no qualifications. To fit the regression model for the relative risk of paediatric burns, additional variables included the Income Deprivation Affecting Children Index (IDACI), % of lone parent households, and % of families with three or more children. Each relative risk was then entered separately into a forward conditional multivariate linear regression model together with variables significantly correlated on univariate analysis. The regression model was checked for multi-collinearity using collinearity diagnostics. Tolerance values of less than 0.2 and variance inflation factor (VIF10) values greater than 5 were considered significant for collinearity. Spatial autocorrelation of the residuals were checked using Moran’s I statistic. A p-value of less than 0.05 was considered statistically significant.

3.

Results

There were a total of 2911 admissions to specialised burns services in Greater London in the 7-year study period. 2100 (72.1%) cases were classified as occurring in the patients’ own homes. There were 1028 paediatric (age 0–14 years) and 1071 adult (15 years) domestic burn injuries. The detailed characteristics of domestic burn injury cases are presented in Table 1. There were a total of 1157 males and 929 females, with gender not having been recorded in 14 cases. The median percentage of total body surface area burned (%TBSA) was 4.0% (inter-quartile range 2.0–7.0%). 33 patients suffered inhalational injuries and 57 patients underwent admission to an intensive care unit (ICU). IMD scores were grouped according to quintiles for the whole of Greater London, with the 1st quintile being the least deprived and the 5th quintile the most deprived. It is observed that the number burn admissions increased for both children and adults towards the more deprived quintiles (Fig. 1). The geographical distribution of IMD scores divided into quintiles is shown on a chloropleth map of London LSOAs in Fig. 2.

10

VIF—Variance inflation factor.

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burns 41 (2015) 437–445

Fig. 1 – Admissions for domestic burn injuries grouped according to IMD quintiles (where 1st quintile = least deprived, 5th quintile = most deprived) for Greater London.

Fig. 2 – Chloropleth map of London LSOAs showing IMD scores divided into quintiles. Higher IMD scores represent more deprived areas.

Fig. 3 – (A) Chloropleth map of London LSOAs showing relative risks of all domestic burn injuries. (B) Histogram showing number of LSOAs across different categories of relative risk. The count of LSOAs in each category is displayed above the corresponding histogram bar.

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burns 41 (2015) 437–445

Fig. 4 – (A) Chloropleth map of London LSOAs showing relative risks of paediatric (0–14 years) domestic burn injury. (B) Histogram showing number of LSOAs across different categories of relative risk. The count of LSOAs in each category is displayed above the corresponding histogram bar.

According to the Census 2011, Greater London had a total population of 8173,941. There were 1531,169 people aged 0–14 years and 6642,772 aged 15 years. Accordingly, the overall rate of domestic burn injury in London was 9.6 per 100,000 per year for children and 2.3 per 100,000 per year for adults. Relative risks of burn injury, produced using Bayesian methods as the best estimate of the smooth standardised incidence ratios (SIRs) detailed in Section 2, were plotted onto chloropleth maps of Greater London LSOAs. Overall, there is a nearly 10-fold variation in relative risk of all domestic burn injuries between LSOAs across London with an impression of

geographic clustering on visual inspection (Fig. 3). Higher relative risks of paediatric domestic burn injury showed apparent geographic clustering in large areas in the northeast of Greater London and sporadic patches in the northwest (Fig. 4). Higher relative risks of adult domestic burn injury also showed local clustering, but in a more sporadic and scattered manner across the whole of Greater London (Fig. 5). In a multivariate linear regression model for analysis of paediatric domestic burns (Table 2), only % BAME ( p = 0.005), Income Deprivation Affecting Children Index ( p < 0.001), Health Deprivation and Disability domain score ( p = 0.031), % of

Table 2 – Multivariate linear regression model for relative risk of burn injuries in children. Variable

B (95% CI)

% BAME Income deprivation affecting children Health deprivation and disability Families with 3+ children Barriers to housing and services

0.006 0.001 0.059 0.007 0.005

(0.005, 0.007) (0.0005, 0.0012) (0.031, 0.084) (0.004, 0.011) (0.001, 0.010)

p-Value

R2 change

Tolerance

0.005

Geographical analysis of socioeconomic factors in risk of domestic burn injury in London 2007-2013.

This study aims to explore the geographical distribution of burn injuries in Greater London and the association of socioeconomic factors in areas at r...
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