Literature DB >> 27098537

The impact of social deprivation on mortality following hip fracture in England and Wales: a record linkage study.

K Thorne1, A Johansen2,3, A Akbari2, J G Williams2, S E Roberts2.   

Abstract

UNLABELLED: We used routine hospital data to investigate whether socially deprived patients had an increased risk of dying following hip fracture compared with affluent patients. We found that the most deprived patients had a significantly increased risk of dying at 30, 90 and 365 days compared with the most affluent patients.
INTRODUCTION: To identify whether social deprivation has any effect on mortality risk after emergency admission with hip fracture and to determine whether any increased mortality observed among deprived groups was associated with patient and hospital-related factors.
METHODS: We used routine, linked hospital inpatient and mortality data for emergency admissions with a hip fracture in both England and Wales between 2004 and 2011. Mortality rates at 30, 90 and 365 days were reported. Logistic regression was used to identify any significant increases in mortality with higher levels of social deprivation and the influence of other risk factors on any increased mortality among the most deprived group.
RESULTS: Mortality rates at 30, 90 and 365 days were 9.3, 17.4 and 29.0 % in England and 8.3, 16.1 and 27.9 % in Wales. Social deprivation was significantly associated with increased mortality in the most deprived quintile compared with the least deprived quintile at 30, 90 and 365 days in England (OR = 1.187, 1.185 and 1.154, respectively) and at 90 and 365 days in Wales (1.135 and 1.203). There was a little interaction between deprivation and other risk factors influencing 30- and 365-day mortality except for patient age, pre-fracture residence and hospital size.
CONCLUSIONS: We demonstrated a positive association between social deprivation and increased mortality at 30 days post-admission for hip fracture in both England and Wales that was still evident at 90 and 365 days. We found little influence of other factors on social inequalities in mortality risk at 30 and 365 days post-admission.

Entities:  

Keywords:  Hip fracture; Mortality; Risk factors; Social deprivation

Mesh:

Year:  2016        PMID: 27098537      PMCID: PMC4981619          DOI: 10.1007/s00198-016-3608-5

Source DB:  PubMed          Journal:  Osteoporos Int        ISSN: 0937-941X            Impact factor:   4.507


Introduction

There were approximately 75,000 hip fractures in the UK in 2012 and this figure is expected to increase in proportion to the number of elderly individuals in the population [1]. Many older people recovering from a hip fracture have coexisting medical, orthopaedic, psychological or social problems that can make operation and rehabilitation a challenge [2]. Approximately one third of patients will die within 1 year of their hip fracture [2, 3], with mortality rates highest in males [4-8] and patients aged over 80 years [7, 8]. Most deaths are due to pre-existing illnesses rather than the fracture itself, reflecting the impact of comorbidities on mortality rates. It is well known that deprived patients tend to have multiple comorbidities [9]. Some research suggests that mortality rates are significantly higher for deprived patients when compared with more affluent patients following admission for hip fracture [6, 10–12] but there is also evidence of no association [13, 14]. Studies have reported advancing age, male gender [6, 10], delays to surgery and comorbidities [10] as independent predictors of mortality in deprived patients but, to date, few studies have examined the impact of socioeconomic inequalities, and those that have do not provide a consensus. Additionally, there has been little published research on the impact of time on surgery, patient residence prior to their fracture, timing of admission or hospital size. We hypothesise that these factors may contribute to an increase in 30- and 365-day mortality rates in the most deprived quintile compared to the least deprived as a consequence of the poor pre-existing physical status, living conditions and access to services for the majority of people residing in deprived areas. With no clear consensus available, we investigated associations between social deprivation and mortality following hip fracture in two comparable populations in the UK, England (population 53 million) and Wales (3 million), using the smaller Welsh population to compare the standard error effects across two similar countries with independently collected data sources. Our first objective was to determine whether there was any increased mortality at 30, 90 and 365 days following admission according to increasing social deprivation. Secondly, we determined whether any increased mortality for deprived groups may be affected by factors such as patient age and gender, timing of admission, time to surgery, the presence of dementia, patient’s pre-fracture residence and hospital size.

Methods

Study design

We used systematic record linkage of national inpatient and mortality data across England and Wales. All records were accessed through the Secure Anonymised Information Linkage (SAIL) databank, which holds records of inpatient admissions in England (Hospital Episode Statistics—HES) and Wales (Patient Episode Database for Wales—PEDW). All records were linked using a unique anonymised linking field (ALF) in Wales and encrypted Hospital Episode Statistic Identifier (HESID) in England that had been attached to the records of each patient using the patient’s National Health Service (NHS) number or other fields such as date of birth, gender or postcode by applying a probabilistic matching algorithm. More details on the SAIL databank and the MACRAL methodology can be found elsewhere [15, 16]. To identify all deaths that occurred following discharge from hospital as well as in hospital, inpatient data were systematically linked to death certificate data from the Office for National Statistics (ONS). For Wales, we also used the Welsh Demographic Service (formerly known as the Welsh Administrative Register) which also registers deaths for confirmatory purposes.

Inclusion and exclusion criteria

We selected all emergency admissions to English and Welsh hospitals where hip fracture was recorded as the principal diagnosis on the discharge record. The International Classification of Diseases 10th revision (ICD-10) codes used for hip fracture were S72.0 (fracture of neck of femur), S72.1 (pertrochanteric fracture) and S72.2 (subtrochanteric fracture). We also included S72.9 (fracture of femur, part unspecified) for patients aged 66+ years on admission, but excluded these fractures of unspecified parts of the femur in people aged under 66 as most would refer to fractures of the shaft (e.g. through sporting and traffic injuries) rather than the neck of the femur. We included patients aged 18 years or over, admitted between January 1, 2004 and December 31, 2011 and followed them up for 12 months to December 31, 2012. Admissions were excluded if they were not emergencies (e.g. elective) or if they occurred within 365 days of a previous hip fracture admission’s discharge date.

Mortality

Mortality rates at 365 days following the admission were used as the primary outcome measure to determine the short-term impact of social deprivation following hip fracture, with mortality at 30 and 90 days as secondary outcome measures. We included deaths from all causes occurring during the inpatient stay and following discharge.

Social deprivation

To measure deprivation, we used the Indices of Multiple Deprivation (IMD) 2007 [17] for England and the Welsh Index of Multiple Deprivation (WIMD) 2008 for Wales [18], both of which have been explicitly designed for assigning area-based levels of deprivation to allow socioeconomic evaluations of local and national populations and are updated regularly to reflect the current population. IMD 2007 consists of seven separate domains of deprivation: income (22.5 %), employment (22.5 %), health and disability (13.5 %), education skills and training (13.5 %), barriers to housing and services (9.3 %), crime (9.3 %) and living environment (9.3 %) and is based on 32,482 Lower Super Output Areas (LSOAs; average population = 1500 each). The WIMD 2008 also consists of seven separate domains of deprivation: ‘income’ (23.5 % contribution), ‘employment’ (23.5 %), ‘health’ (14 %), ‘education’ (14 %), ‘access to services’ (10 %), ‘housing’ (5 %), ‘physical environment’ (5 %) and ‘community safety’ (5 %) and is based on 1896 LSOAs. Both indexes provide a deprivation score which was ranked and assigned to one of the five deprivation quintiles (I = least deprived and V = most deprived quintile).

Risk factors

We assessed a number of key risk factors to determine whether they significantly mediated the relationship between social deprivation and mortality at both 30 and 365 days following admission by using logistic regression. We analysed the impact on mortality for each risk factor, stratified by each subgroup within that risk factor, comparing the least and most deprived cases, using the least deprived quintile as the reference group.

Patient demographics

The patient’s age on admission was collected for each case. Age was grouped into <65 years, 65 to 74 years, 75 to 84 years and 85+ years. The patient’s gender was also recorded.

Timing of admission

We investigated any impact of the day of admission on mortality by assigning weekdays (Monday 00:00 to Friday 23:59), weekends (Saturday 00:00 to Sunday 23:59) and public holidays (eight per year) which were prioritised over weekdays and weekends in this classification. We also investigated the season of admission (winter = Dec to Feb; spring = Mar to May; summer = Jun to Aug; autumn = Sept to Nov) and calendar years of admission (grouped by 2004–2005, 2006–2008 and 2009–2011).

Hospital size

Hospital size at the time of admission was collected from the Health and Social Care Information centre (HSCIC) for England and from Statistics for Wales (StatsWales) for Welsh patients and grouped into 100–399 (small hospital), 400–599 (medium) or 600+ beds (large).

Time to surgery

Time to surgery was calculated by determining the difference between the admission date and the date of the first hip fracture-related operation, using the following Office of Population Censuses and Surveys Classification of Surgical Operations and Procedures (4th revision) (OPCS-4) codes: W19.1 (primary open reduction of fracture of neck of femur and open fixation using pin and plate), W24.1 (closed reduction of intracapsular fracture of neck of femur and fixation using nail or screw), W37–W39 (total prosthetic replacement), W46–W48 (prosthetic replacement of head of femur), W58 (resurfacing of hip joint) or W93–95 (hybrid prosthetic replacement). Some of these procedures are performed for other indications (e.g. osteoarthritis), but we included them only when they had been performed as part of the emergency hip fracture admission. We grouped the time to surgery into three categories to reflect NICE guidelines [1], namely surgery on the day of admission or the next day, on the third day or after the third day.

Dementia

In our analysis, we defined dementia using ICD-10 codes F00–F03, F05.1 and G30, during the index admission or any admission during the previous 5 years.

Pre-fracture residence

As a proxy for pre-fracture mobility, we categorised patients according to their pre-fracture residence: whether they had previously been living in their own home, in a nursing/residential care home or were transferred from another hospital.

Patient comorbidities

When investigating mortality, we also adjusted for the impact of age group, gender and comorbidities. Specifically, we adjusted for any impact of the following 11 major patient comorbidities using ICD-10 codes recorded in any diagnostic position during the admission or within the previous 5 years from inpatient care records where available: ischaemic heart disease (ICD-10 I20–I25) or other cardiovascular diseases (I00–I15, I26–I52), cerebrovascular disease (I60–I69), other circulatory diseases (I70–I99), malignancies (C00–C97), chronic obstructive pulmonary disease (COPD) (J40–J44), asthma (J45–J46), diabetes (E10–E14), dementia (F00–F03, F05.1, G30), liver disease (K70–K77) and renal failure (N17–N19).

Methods of analysis

The main study outcome measures were percentage mortality rates, the odds of mortality for the most deprived versus the least deprived and impact of risk factors at 30, 90 and 365 days following admission for each condition using logistic regression. We reported key demographic characteristics for the most and least deprived cases including age, gender, fracture type and comorbidities and tested for statistical significance using independent sample t tests and Pearson’s chi-squared tests. Significance was measured at the conventional 5 % level. Logistic regression was also used to establish how any higher mortality for deprived groups at 30 and 365 days may be correlated with the following key risk factors: patient age and gender, whether the patient had dementia, the day type, season and year group of admission, hospital size, time to surgery and pre-fracture residence. To do this, we compared mortality in the least and most deprived quintiles, using the least deprived quintile as the reference category, for each stratum of each risk factor. The logistic regression mortality odds ratios were presented with 95 % confidence intervals. Significance was measured at the conventional 5 % level. Thirdly, logistic regression was used to test for any interaction effects on mortality between social deprivation and each of the study risk factors. This would highlight whether there were any significant differences between the mortality odds ratios within each risk factor. All logistic regression analyses were adjusted for age, gender and the 11 patient comorbidities. We also adjusted the model so that patients with no previous inpatient admissions in the last 5 years, meaning no comorbidities were recorded, did not bias the results. A Bonferroni correction was applied to account for multiple statistical tests. Results were displayed in tables to indicate whether they were significant before and after the correction was applied.

Results

Between January 2004 and December 2011, there were 455,862 people admitted with hip fracture in England and 29,733 in Wales. In England, the mean age at admission was 80.7 years ± 11.6 and males accounted for 26.2 % of cases. In Wales, the mean age was 80.4 years ± 11.1 and males accounted for 25.9 % of cases. Gender was missing for eight cases from England and no cases from Wales. Social deprivation scores could not be calculated for 5447 cases who did not live in England but were admitted to English hospitals, and 966 cases who did not live in Wales but were admitted to Welsh hospitals. These were not included in the analyses. No other data items in the analysis were missing from the dataset.

Baseline differences between affluent and deprived quintiles

We found significant differences between the most affluent and the least deprived quintiles for mean age at admission, fracture type and many comorbidities and, for England only, gender and hospital length of stay (see Table 1). When compared with the least deprived cases, the most deprived cases were more likely to be male, younger, presenting with trochanteric fractures and, with the exception of malignancies, were more likely to have comorbidities. In England, they also had a longer inpatient stay, though we did not observe this in Wales.
Table 1

Demographics of patients in the least and most deprived quintiles for England and Wales

EnglandWales
Least deprivedMost deprivedSig.Least deprivedMost deprivedSig.
No. of cases86,14885,42253335765
Mean age in years (SD)81.5 (10.9)78.8 (12.7) <0.001 81.5 (10.3)79.2 (11.6) <0.001
Gendera
 Male25.7 %28.6 % <0.001 26.0 %27.5 %0.079
 Female74.3 %71.4 %74.0 %72.5 %
30-day mortality rate (crude %)8.5 %9.7 %8.2 %9.2 %
90-day mortality rate (crude %)16.2 %18.1 %15.9 %17.2 %
365-day mortality rate (crude %)27.3 %30.1 %26.5 %29.8 %
Fracture type
 Fracture of neck of femur73.6 %71.7 % <0.001 72.8 %67.8 % <0.001
 Pertrochanteric fracture22.3 %24.3 %23.7 %28.3 %
 Subtrochanteric fracture3.2 %3.2 %2.9 %3.3 %
 Fracture of femur, part unspecified0.8 %0.8 %0.6 %0.6 %
Mean spell duration (SD)21.6 (22.5)24.7 (25.4) <0.001 23.9 (33.2)23.6 (30.6)0.704
Comorbidities during previous 5 years
 Acute myocardial infarction5.5 %6.5 % <0.001 6.8 %7.1 %0.525
 Cerebrovascular disease13.6 %15.7 % <0.001 17.4 %18.2 %0.275
 Other circulatory disease18.0 %21.1 % <0.001 30.9 %31.8 %0.316
 Malignancies13.2 %12.7 % 0.003 16.2 %14.5 % 0.011
 Liver disease1.6 %3.3 % <0.001 1.4 %2.9 % <0.001
 COPD8.9 %18.8 % <0.001 13.0 %21.7 % <0.001
 Asthma8.1 %11.7 % <0.001 9.9 %14.8 % <0.001
 Diabetes11.6 %15.3 % <0.001 13.0 %16.9 % <0.001
 Renal failure10.8 %13.5 % <0.001 10.6 %11.1 %0.375
 Dementia23.1 %24.3 % <0.001 22.1 %23.8 % 0.042

Significance was measured at the 5 % level using chi-squared tests or t tests

All significant results are set in italic

aGender was missing for eight cases in England

Demographics of patients in the least and most deprived quintiles for England and Wales Significance was measured at the 5 % level using chi-squared tests or t tests All significant results are set in italic aGender was missing for eight cases in England

Mortality, demographics and social deprivation

In England, mortality at 30 days was 9.3 %, at 90 days was 17.4 % and at 365 days was 29.0 % whilst in Wales, the rates were 8.3, 16.1 and 27.9 %, respectively. Mortality rates at 30 days were highest in the over 85 age group (13.6 % in England and 11.5 % in Wales) and higher in men (12.2 % in England and 11.0 % in Wales) compared with women (8.3 and 7.4 %). After Bonferroni corrections were applied, social deprivation was significantly associated with an increase in mortality at 30 days in England (most deprived = 1.187 compared with least deprived) but the increase was not significant in Wales (1.136). At 90 and 365 days, mortality rates were significantly increased in both populations (1.185 and 1.154 in England, and 1.135 and 1.203 in Wales; see Table 2).
Table 2

Thirty-day mortality odds ratios at 30, 90 and 365 days following hip fracture according to age, gender and social deprivation, 2004 to 2012

Risk factorAdjusted† 30-day OR (95 % CI)Adjusted† 90-day OR (95 % CI)Adjusted† 365-day OR (95 % CI)
England
 Gendera MaleReferenceReferenceReference
Female 0.608 (0.595, 0.622)* 0.641 (0.629, 0.653)* 0.651 (0.640, 0.661)*
 Social deprivationb I (least deprived)ReferenceReferenceReference
II 1.094 (1.058, 1.131)* 1.075 (1.048, 1.104)* 1.046 (1.023, 1.070)*
III 1.116 (1.079, 1.153)* 1.097 (1.069, 1.126)* 1.075 (1.052, 1.099)*
IV 1.157 (1.119, 1.196)* 1.153 (1.123, 1.183)* 1.122 (1.097, 1.147)*
V (most deprived) 1.187 (1.147, 1.228)* 1.185 (1.154, 1.217)* 1.154 (1.128, 1.181)*
Wales
 GenderMaleReferenceReferenceReference
Female 0.641 (0.583, 0.705)* 0.664 (0.616, 0.714)* 0.661 (0.620, 0.705)*
 Social deprivationb I (least deprived)ReferenceReferenceReference
II0.993 (0.863, 1.142)0.970 (0.871, 1.081)1.093 (0.998, 1.198)
III0.981 (0.856, 1.123)1.046 (0.943, 1.160) 1.132 (1.037, 1.237)
IV0.963 (0.838, 1.106)1.089 (0.981, 1.209) 1.151 (1.053, 1.259)
V (most deprived)1.136 (0.991, 1.302) 1.135 (1.022, 1.261) 1.203 (1.100, 1.317)*

Italic font denotes significance at the 5 % level

*Denotes significance after applying a Bonferroni correction for each condition (p ≤ 0.00167)

†The OR for gender is adjusted for age group and comorbidities. All other factors were adjusted for age group, gender and comorbidities

aGender was missing for 26 cases in England

bSocial deprivation scores were missing for 5447 cases in England and 966 cases in Wales

Thirty-day mortality odds ratios at 30, 90 and 365 days following hip fracture according to age, gender and social deprivation, 2004 to 2012 Italic font denotes significance at the 5 % level *Denotes significance after applying a Bonferroni correction for each condition (p ≤ 0.00167) †The OR for gender is adjusted for age group and comorbidities. All other factors were adjusted for age group, gender and comorbidities aGender was missing for 26 cases in England bSocial deprivation scores were missing for 5447 cases in England and 966 cases in Wales

Effect of factors on the increased 365-day mortality with social deprivation

Tables 3 and 4 report the mortality rates for quintiles I and V, along with the adjusted 30- and 365-day mortality risk associated with each of the factors listed for England and Wales, respectively.
Table 3

Mortality risk at 30 and 365 days following admission for hip fracture in England according to deprivation and key risk factors

Risk factorNo. of admissions30-day mortality rate (%)Adjusted†30-day mort OR(95 % CI)365-day mortality rate (%)Adjusted† 365-day mort OR(95 % CI)
Least deprivedMost deprivedLeast deprivedMost deprivedLeast deprivedMost deprived
Age<65 years625910,4321.72.5 1.151 0.905, 1.464 6.29.8 1.209 1.052, 1.389
65–74 years980312,3313.55.4 1.208 1.050, 1.390 13.019.2 1.215 1.119, 1.319
75–84 years31,30531,3216.49.1 1.269 1.193, 1.350 22.329.0 1.216 1.170, 1.265
85+ years38,78131,33812.514.4 1.138 1.088, 1.190 38.442.2 1.090 1.056, 1.125
GenderMale22,14824,44311.911.4 1.130 1.063, 1.200 34.033.21.1431.094, 1.195
Female63,99460,9777.39.1 1.217 1.166, 1.269 25.028.91.1571.125, 1.189
Day of the weekWeekdays (Mon–Fri)61,71660,8298.59.71.1791.132, 1.22827.330.11.1501.119, 1.182
Weekends (Sat–Sun)22,51122,6688.39.71.2181.139, 1.30427.230.01.1561.105, 1.209
Public holidays192119259.210.21.2040.959, 1.51128.330.61.2101.036, 1.414
Season of admissionWinter22,48222,5479.310.51.1611.088, 1.23928.030.81.1411.091, 1.193
Spring21,48221,3058.49.51.1881.108, 1.27427.029.81.1681.115, 1.223
Summer20,96520,6727.89.31.2281.142, 1.32026.929.31.1301.077, 1.184
Autumn21,21920,8988.39.61.1861.105, 1.27227.430.51.1721.118, 1.229
Year of admission2004–200519,86721,3619.810.71.1251.052, 1.20329.331.51.1161.065, 1.169
2006–200831,89232,0229.110.41.1851.121, 1.25228.431.41.1691.126, 1.214
2009–201134,38932,0397.28.41.1881.120, 1.26125.327.91.1071.065, 1.150
Hospital size100–399 beds13,28210,6578.49.2 1.238 1.162, 1.319 27.429.2 1.077 1.012, 1.147
400–599 beds29,37122,5418.39.8 1.135 1.070, 1.205 26.830.4 1.028 1.158, 1.261
600+ beds25,94833,7938.59.5 1.265 1.175, 1.362 27.829.7 1.087 1.044, 1.131
Time to surgerySame day12,01410,1596.16.31.1050.985, 1.23922.723.81.1151.040, 1.196
Next day28,12825,7926.27.11.1911.110, 1.27823.125.41.1221.074, 1.171
Third day12,01911,2417.27.81.1341.024, 1.25525.827.51.0941.025, 1.166
After 3 days12,94814,2208.48.91.1311.035, 1.23533.134.61.0971.038, 1.159
DementiaNo66,21464,6817.69.11.2401.189, 1.29222.225.41.2261.192, 1.261
Yes19,93420,74111.311.7NANA44.444.61.0160.975, 1.058
Pre-fracture residenceOwn home78,71379,8498.49.7 1.201 1.159, 1.245 27.229.81.1491.122, 1.178
Nursing/residential home799149216.115.1 0.851 0.664, 1.092 47.949.51.0200.850, 1.224
Transfer592235179.18.4 0.994 0.850, 1.163 27.928.61.0990.991, 1.219

Quintile I was used as the reference group. The ORs of quintile V are reported in the table

NA indicates regression analysis was not possible

Italic font denotes significant interaction effects at the 5 % level

†The OR for age group was adjusted for gender and comorbidities; gender was adjusted for age group and comorbidities; all other factors were adjusted for age group, gender and comorbidities

Table 4

Mortality risk at 30 and 365 days following admission for hip fracture in Wales according to deprivation and key risk factors

Risk factorNo. of admissions30-day mortality rate (%)Adjusted† 30-day mort OR(95 % CI)365-day mortality rate (%)Adjusted† 365-day mort OR(95 % CI)
Least deprivedMost deprivedLeast deprivedMost deprivedLeast deprivedMost deprived
Age<65 years3556000.83.0 3.297 0.927, 11.28 5.19.0 1.476 0.798, 2.732
65–74 years6409163.66.7 1.711 1.026, 2.854 12.018.0 1.438 1.046, 1.977
75–84 years202021436.49.7 1.501 1.183, 1.905 22.530.6 1.421 1.223, 1.652
85+ years2318210612.311.7 0.886 0.734, 1.069 37.439.9 1.036 0.912, 1.177
GenderMale1386158411.011.81.2270.966, 1.55933.233.41.1991.008, 1.427
Female394741817.38.31.1040.932, 1.30824.228.41.2221.098, 1.361
Day of the weekWeekdays (Mon–Fri)386241207.99.7 1.280 1.088, 1.506 26.630.41.2271.103, 1.365
Weekends (Sat–Sun)134915169.18.1 0.904 0.686, 1.192 26.128.21.1770.979, 1.414
Public holidays12212912.36.2 0.547 0.205, 1.459 27.927.91.2530.639, 2.457
Season of admissionWinter139115609.39.71.0900.840, 1.41428.530.41.2161.021, 1.448
Spring132614408.79.51.1160.849, 1.46626.229.91.2010.998, 1.445
Summer128513877.89.01.1480.862, 1.53026.129.81.2061.003, 1.450
Autumn133113787.48.61.2400.925, 1.66425.228.71.2211.011, 1.475
Year of admission2004–2005118814208.710.61.3981.059, 1.84724.731.61.5711.297, 1.903
2006–2008207621588.78.60.9820.785, 1.22927.830.31.1581.001, 1.339
2009–2011206921877.79.01.1820.940, 1.48626.328.01.0940.941, 1.272
Hospital size100–399 beds1892646.39.81.3161.055, 1.64223.329.2 1.421 0.844, 2.392
400–599 beds166626858.810.50.9610.791, 1.16728.330.5 1.231 1.060, 1.430
600+ beds326025528.68.51.9330.446, 8.38226.729.3 1.123 0.989, 1.274
Time to surgerySame day6717176.17.11.1840.754, 1.85720.024.41.3641.026, 1.813
Next day161518247.18.21.2350.947, 1.60923.426.11.1981.010, 1.421
Third day6656625.76.51.2000.746, 1.92824.228.41.2870.980, 1.689
After 3 days10099867.38.31.2170.861, 1.72032.035.41.2570.992, 1.493
DementiaNo415343957.88.41.1140.945, 1.31322.224.81.2341.105, 1.378
Yes1180137010.112.01.2340.955, 1.59541.945.51.1700.993, 1.377
Pre-fracture residenceOwn home489952577.88.8 1.172 1.011, 1.360 25.528.4 1.204 1.097, 1.331
Nursing/residential home23629920.815.7 0.631 0.392, 1.017 51.751.2 0.923 0.641, 1.331
Transfer1771864.59.1 1.860 0.690, 5.016 20.933.9 2.062 1.209, 3.517

Quintile I was used as the reference group. The ORs of quintile V are reported in the table

Italic font denotes significant interaction effects at the 5 % level

†The OR for age group was adjusted for gender and comorbidities; gender was adjusted for age group and comorbidities; all other factors were adjusted for age group, gender and comorbidities

Mortality risk at 30 and 365 days following admission for hip fracture in England according to deprivation and key risk factors Quintile I was used as the reference group. The ORs of quintile V are reported in the table NA indicates regression analysis was not possible Italic font denotes significant interaction effects at the 5 % level †The OR for age group was adjusted for gender and comorbidities; gender was adjusted for age group and comorbidities; all other factors were adjusted for age group, gender and comorbidities Mortality risk at 30 and 365 days following admission for hip fracture in Wales according to deprivation and key risk factors Quintile I was used as the reference group. The ORs of quintile V are reported in the table Italic font denotes significant interaction effects at the 5 % level †The OR for age group was adjusted for gender and comorbidities; gender was adjusted for age group and comorbidities; all other factors were adjusted for age group, gender and comorbidities There was a significant interaction with age group at 30 and 365 days in England (p < 0.001 for both time points) and Wales (p < 0.001 and p = 0.008, respectively), with patients aged over 85 in the most deprived quintile showing a significant and lower odds ratio than the other age groups at 30 and 365 days in England (see Table 3) and Wales (see Table 4). There was also a significant interaction with gender at 30 days in England (p = 0.001), with females in the most deprived quintile having a significantly higher mortality risk. There was no significant interaction effect at 365 days, with males and females showing similar mortality risk. In Wales, males had a higher risk at 30 days and females at 365 days, and neither of which showed a significant interaction effect. There was a significant interaction effect with weekday at 30 days in Wales (p = 0.024), with patients in the most deprived quintile (compared with the least deprived quintile) admitted Monday–Friday having a significantly higher mortality risk than those admitted at the weekend or public holidays. However, there was no significant interaction effect at 365 days, nor for England at 30 or 365 days. There was a significant interaction effect with hospital size at 30 and 365 days in England (p = 0.029 and p < 0.001, respectively) and for 365 days in Wales (p = 0.006). In England, mortality risk for patients from the most deprived quintile was greatest for large (600+ beds) hospitals at both 30 and 365 days. The medium-sized hospitals had the lowest risk of all at 30 and 365 days. In Wales, there was no significant interaction effect at 30 days but at 365 days, the small hospitals (100–399 beds) had a significantly higher mortality risk than the other hospital groups. Next day, surgery had the highest odds ratio for 30 and 365 days in England and 30 days in Wales, but there was no significant interaction effect between social deprivation and time to surgery at 30 or 365 days for England or Wales. In England, there were insufficient numbers to calculate the odds ratio for patients with dementia who died within 30 days. At 365 days, not having dementia appeared to significantly increase the mortality risk for the most deprived compared with the least deprived quintile. In Wales, the same effect was seen at 365 days but at 30 days, neither odds ratio was significant. There were no significant interaction effects noted. There was a significant interaction effect for 30-day mortality in England and both 30- and 365-day mortality in Wales. In England, patients from the most deprived quintile admitted from their own home had a significantly higher 30-day mortality risk than patients admitted from a nursing or residential home, or who were transferred in. At 365 days, the mortality risk was still the highest in this group but not significantly so. In Wales, there was a significantly higher risk of 30- and 365-day mortality for patients transferred to the hospital.

Discussion

We found that social deprivation was significantly associated with higher mortality at 30, 90 and 365 days following an emergency admission for hip fracture in England and at 90 and 365 days in Wales. We also found that patient age, hospital size and pre-fracture residence were significantly associated with mortality in those who were from deprived areas in both populations. Our 30-day mortality rates of 9.3 % in England and 8.3 % in Wales were comparable with those reported by other hip fracture studies in the UK [10, 19–23]. The same was true for our 365-day mortality rates of 29.0 % in England and 27.9 % in Wales [21-25]. The significant association we found between mortality risk and social deprivation has also been reported by other UK [3, 6, 10, 26] and international [6] studies. Our data showed that deprived patients were younger on admission. The influence of age on mortality after hip fracture has been extensively described [4–8, 10, 21, 27–30], and our study suggests that the increased mortality risk seen in these deprived patients reflects an increased rate of comorbidities compared to the most affluent patients—a trend that has been reported by others [12]. Other key predictors of mortality following hip fracture include male gender [4–8, 10, 21, 27–30], comorbidities [4, 8, 31, 32], dementia [8, 30], osteoporosis [4], fracture severity [8, 21, 27, 31], surgical delays [10, 32] and post-operative complications [32], living in a nursing or residential home [8], poor pre-injury walking capacity [8] and poor social contact [7]. We hypothesised that many of these predictors would be influenced by patients’ social deprivation status and might increase mortality risk for the most deprived patients. Unfortunately, HES and PEDW do not capture facture severity, walking capacity, post-operative complications or social contact, and comorbidities are not rigorously recorded on records in either country. For example, only 10 % of women with a hip fracture had osteoporosis recorded as a comorbidity. Consequently, we were unable to include these factors into any analyses. Dementia has been reported as playing a major role in increasing mortality risk in patients with hip fracture as patients have a lower probability of functional recovery at discharge and 6 months post-discharge [33]. Our study showed an increased risk of mortality within 30 days, but not at 365 days, suggesting that the impact of dementia is most crucial during the acute admission, surgery and rehabilitation. Mortality risk was significantly different in England at 30 and 365 days with the largest hospitals showing the higher mortality rates for deprived patients. In Wales, higher mortality rates were seen in the largest hospitals at 30 days, although this was not significantly different to the other hospital groups. However, at 365 days, it was the smaller hospitals whose mortality rates were significantly higher than the other groups. Time to surgery and complications after surgery contribute to increased mortality rates. Whilst we were able to investigate the impact of surgical delays according to deprivation status, the administrative data lacked sufficient detail to explore post-operative complications, but there is evidence to suggest that low income is associated with a higher risk of acute medical events and infections [13]. Our data showed that the most deprived patients had a higher mortality rate following surgery than the most affluent patients at 30 and 365 days, and that this difference increased with greater delay to surgery. However, there was no significant interaction effect, so we cannot conclude that the mortality risks were significantly different according to time to surgery. A meta-analysis of hip fracture studies reported that operating beyond 48 h may increase the odds of 30-day mortality by 41 % and of 365-day mortality by 32 % [34], but this remains a complex question since many delays to surgery are a consequence of comorbidities that need assessment or treatment before surgery and anaesthesia can go ahead [35]. People from deprived areas are known to be at higher risk of multiple comorbidities than their affluent counterparts [9], but there is also evidence that socioeconomic deprivation is associated with lower rates of early intervention [6, 13]. If so, then the additional delays experienced by deprived patients might result in higher mortality rates for this group. The patient’s residence pre-injury will affect mortality risks, with people admitted from a nursing or residential care home, experiencing higher mortality [21]. When we examined patients’ pre-admission residence, we found that in England, 30- and 365-day mortality rates for people admitted from home were higher for deprived than for affluent patients, significantly so at 30 days. In Wales, the highest mortality at both 30 and 365 days was seen in deprived patients transferred to the hospital from another healthcare provider, compared with affluent patients. Major strengths of the study are its size, covering more than 455,000 cases of hip fracture in England and 29,700 in Wales. The methodology was based on systematic, validated record linkage of inpatient and death certificate to identify all admissions and all deaths that occur during the inpatient stay and following discharge from hospital. Finally, using Welsh data allowed us to compare our findings in a similar, albeit smaller population. As with other large-scale studies that used NHS administrative health data, this study lacked detailed information about patient disease history or any severity indicators. We were also unable to determine the exact time elapsed until surgery was performed as this information is only recorded at date level with no time field available in either HES or PEDW. We did not combine both populations as the measures of deprivation used in each country were based on different domains with no validated method for merging the two. Whilst the inclusion of alcohol and substance abuse would have been useful additions to our modelling, the quality of that data was extremely poor and could not be used. Additionally, we were unable to use the Charlson Comorbidity Index in accordance with its requirements as the UK regulations prohibit the access of HIV status in routine data. However, the comorbidities used in this study were based on other measures in that index wherever possible. Social deprivation refers to problems caused by a general lack of resources and opportunities and not just money. The association between social deprivation and increased mortality risk is multifaceted, and a patient’s pre-existing and baseline clinical and psychological status may contribute to any relationship between social deprivation and mortality. Mortality following hip fracture is usually attributed to underlying ill health [1], but poor social contact pre-injury has also been linked with increased mortality risk [7], and other deprivation-related factors including reduced resources, lower education status, poor lifestyle and social contact, reduced likelihood of preventative medication, and poor mental health, particularly dementia, may also play a part. However, when interpreting these findings of an association between deprivation and increased mortality, it is important to remember the ecological fallacy: not everyone living in a deprived area is deprived, and that not all deprived people live in deprived areas.

Conclusions

We have demonstrated a clear association between social deprivation and increased mortality following emergency admission for hip fracture in the two UK populations. The study findings also suggest that patient age, hospital size and pre-fracture residence are factors that play a part in this association in both English and Welsh populations.
  30 in total

1.  Admission rates and in-hospital mortality for hip fractures in England 1998 to 2009: time trends study.

Authors:  Tai-Yin Wu; Min-Hua Jen; Alex Bottle; Chen-Kun Liaw; Paul Aylin; Azeem Majeed
Journal:  J Public Health (Oxf)       Date:  2010-10-05       Impact factor: 2.341

2.  Outcome following hip fracture: post-discharge residence and long-term mortality.

Authors:  Antony Johansen; Maizura Mansor; Sue Beck; Heather Mahoney; Suzanne Thomas
Journal:  Age Ageing       Date:  2010-06-28       Impact factor: 10.668

3.  Early surgery for patients with a fracture of the hip decreases 30-day mortality.

Authors:  C P Bretherton; M J Parker
Journal:  Bone Joint J       Date:  2015-01       Impact factor: 5.082

Review 4.  Hip fracture audit: the Nottingham experience.

Authors:  N Gunasekera; C Boulton; C Morris; C Moran
Journal:  Osteoporos Int       Date:  2010-11-06       Impact factor: 4.507

5.  Risk factors for in-hospital post-hip fracture mortality.

Authors:  Steven A Frost; Nguyen D Nguyen; Deborah A Black; John A Eisman; Tuan V Nguyen
Journal:  Bone       Date:  2011-06-13       Impact factor: 4.398

6.  A prospective study on socioeconomic aspects of fracture of the proximal femur.

Authors:  M A Schürch; R Rizzoli; B Mermillod; H Vasey; J P Michel; J P Bonjour
Journal:  J Bone Miner Res       Date:  1996-12       Impact factor: 6.741

7.  The effect of becoming a major trauma centre on outcomes for elderly hip fracture patients.

Authors:  Lynne V Barr; Madhavi Vindlacheruvu; Chris R Gooding
Journal:  Injury       Date:  2014-12-15       Impact factor: 2.586

8.  Early mortality after hip fracture: is delay before surgery important?

Authors:  Christopher G Moran; Russell T Wenn; Manoj Sikand; Andrew M Taylor
Journal:  J Bone Joint Surg Am       Date:  2005-03       Impact factor: 5.284

9.  Effects of socioeconomic position on 30-day mortality and wait for surgery after hip fracture.

Authors:  Anna Patrizia Barone; Danilo Fusco; Paola Colais; Mariangela D'Ovidio; Valeria Belleudi; Nera Agabiti; Chiara Sorge; Marina Davoli; Carlo Alberto Perucci
Journal:  Int J Qual Health Care       Date:  2009-10-19       Impact factor: 2.038

10.  Time trends and demography of mortality after fractured neck of femur in an English population, 1968-98: database study.

Authors:  Stephen E Roberts; Michael J Goldacre
Journal:  BMJ       Date:  2003-10-04
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  16 in total

Review 1.  Understanding the role of social factors in recovery after hip fractures: A structured scoping review.

Authors:  Mohammad Auais; Fadi Al-Zoubi; Alyssa Matheson; Kelcie Brown; Jay Magaziner; Simon D French
Journal:  Health Soc Care Community       Date:  2019-08-25

2.  Socio-economic inequalities in fragility fracture outcomes: a systematic review and meta-analysis of prognostic observational studies.

Authors:  G Valentin; S E Pedersen; R Christensen; K Friis; C P Nielsen; A Bhimjiyani; C L Gregson; B L Langdahl
Journal:  Osteoporos Int       Date:  2019-08-30       Impact factor: 4.507

Review 3.  Antihypertensive Drugs and Risk of Bone Fractures.

Authors:  Maria Velliou; Elias Sanidas; Aliki Zografou; Dimitrios Papadopoulos; Nikolaos Dalianis; John Barbetseas
Journal:  Drugs Aging       Date:  2022-06-27       Impact factor: 4.271

4.  Prevalence of and factors associated with adopting bone health promoting behaviours among people with osteoporosis in Taiwan: a cross-sectional study.

Authors:  Po-Han Chen; Ming-Shyan Lin; Tung-Jung Huang; Mei-Yen Chen
Journal:  BMJ Open       Date:  2017-09-25       Impact factor: 2.692

5.  The impact of hip fracture on mortality in Estonia: a retrospective population-based cohort study.

Authors:  Mikk Jürisson; Mait Raag; Riina Kallikorm; Margus Lember; Anneli Uusküla
Journal:  BMC Musculoskelet Disord       Date:  2017-06-05       Impact factor: 2.362

6.  Socioeconomic Inequality in One-Year Mortality of Elderly People with Hip Fracture in Taiwan.

Authors:  I-Lin Hsu; Chia-Ming Chang; Deng-Chi Yang; Ya-Hui Chang; Chia-Chun Li; Susan C Hu; Chung-Yi Li
Journal:  Int J Environ Res Public Health       Date:  2018-02-16       Impact factor: 3.390

7.  Cortical Thickness Index of the Proximal Femur: A Radiographic Parameter for Preliminary Assessment of Bone Mineral Density and Osteoporosis Status in the Age 50 Years and Over Population.

Authors:  Bao Nt Nguyen; Hironobu Hoshino; Daisuke Togawa; Yukihiro Matsuyama
Journal:  Clin Orthop Surg       Date:  2018-05-18

8.  Renin-angiotensin system inhibitors and risk of fractures: a prospective cohort study and meta-analysis of published observational cohort studies.

Authors:  Setor K Kunutsor; Ashley W Blom; Michael R Whitehouse; Patrick G Kehoe; Jari A Laukkanen
Journal:  Eur J Epidemiol       Date:  2017-07-27       Impact factor: 8.082

9.  Relative survival following hemi-and total hip arthroplasty for hip fractures in Sweden.

Authors:  Szilard Nemes; Dennis Lind; Peter Cnudde; Erik Bülow; Ola Rolfson; Cecilia Rogmark
Journal:  BMC Musculoskelet Disord       Date:  2018-11-23       Impact factor: 2.362

10.  Selective serotonin reuptake inhibitor use and mortality, postoperative complications, and quality of care in hip fracture patients: a Danish nationwide cohort study.

Authors:  Stine Bakkensen Bruun; Irene Petersen; Nickolaj Risbo Kristensen; Deirdre Cronin-Fenton; Alma Becic Pedersen
Journal:  Clin Epidemiol       Date:  2018-08-27       Impact factor: 4.790

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