Impact of socio-economic status on hospital length of stay following injury: a multicenter cohort study

Background

Injury is second only to cardiovascular disease in terms of acute care costs in North America. One key to improving injury care efficiency is to generate knowledge on the determinants of resource use. Socio-economic status (SES) is a documented risk factor for injury severity and mortality but its impact on length of stay (LOS) for injury admissions is unknown. This study aimed to examine the relationship between SES and LOS following injury.This multicenter retrospective cohort study was based on adults discharged alive from any trauma center (2007–2012; 57 hospitals; 65,486 patients) in a Canadian integrated provincial trauma system. SES was determined using ecological indices of material and social deprivation. Mean differences in LOS adjusted for age, gender, comorbidities, and injury severity were generated using multivariate linear regression.

Results

Mean LOS was 13.5 days. Patients in the highest quintile of material/social deprivation had a mean LOS 0.5 days (95 % CI 0.1-0.9)/1.4 days (1.1-1.8) longer than those in the lowest quintile. Patients in the highest quintiles of both social and material deprivation had a mean LOS 2.6 days (1.8-3.5) longer than those in the lowest quintiles.

Conclusions

Results suggest that patients admitted for traumatic injury who suffer from high social and/or material deprivation have longer acute care LOS in a universal-access health care system. The reasons behind observed differences need to be further explored but may indicate that discharge planning should take patient SES into consideration.

     

Geographic variation in work injuries: a multilevel analysis of individual-level data and area-level factors within Canada

PurposeThis study sought to examine provincial variation in work injuries and to assess whether contextual factors are associated with geographic variation in work injuries.MethodsIndividual-level data from the 2003 and 2005 Canadian Community Health Survey was obtained for a representative sample of 89,541 Canadians aged 15 to 75 years old who reported working in the past 12 months. A multilevel regression model was conducted to identify geographic variation and contextual factors associated with the likelihood of reporting a medically attended work injury, while adjusting for demographic and work variables.ResultsProvincial differences in work injuries were observed, even after controlling for other risk factors. Workers in western provinces such as Saskatchewan (adjusted odds ratio [AOR], 1.30; 95% confidence interval [CI], 1.09–1.55), Alberta (AOR, 1.31; 95% CI, 1.13–1.51), and British Columbia (AOR, 1.46; 95% CI, 1.26–1.71) had a higher risk of work injuries compared with Ontario workers. Indicators of area-level material and social deprivation were not associated with work injury risk.ConclusionsProvincial differences in work injuries suggest that broader factors acting as determinants of work injuries are operating across workplaces at a provincial level. Future research needs to identify the provincial determinants and whether similar large area–level factors are driving work injuries in other countries.     

Rural and urban variation in psychological distress among adults: results of the 2014–2015 Eastern Townships Population Health Survey (ETPHS)

ObjectiveA growing number of people live in urban areas. Urbanization has been associated with an increased prevalence of mental disorders, but which mechanisms cause this increase is unknown. Psychological distress is a good indicator of mental health. This study sought to examine the relationship between urbanization and distress among adults in the Eastern Townships (southern region of Quebec, Canada).MethodIn the 2014–2015 Eastern Townships Population Health Survey (N = 10,687 adults living in one of the 96 Eastern Townships communities), distress was measured with the K6 distress scale (≥ 7). Urbanization was estimated by the residential density of the community treated in quintiles. Logistic regression analyses were carried out with adjustments for individual and environmental characteristics.ResultsWomen, young people aged 18–24, single parents, those without diplomas, those without a job, those with < $20,000 in income, adults with two or more chronic physical illnesses, adults with bad perceived health, or those living in disadvantaged neighbourhoods exhibited more distress. The unadjusted estimate between density and distress is only significant for the fifth quintile when compared with the first quintile (OR 1.23; 95% CI: 1.06–1.42). The relationship is practically the same after controlling for individual characteristics but decreases considerably after controlling for environmental characteristics (lack of trees, social deprivation, intersection density, vegetation index, and land use mix).ConclusionThis study was the first to examine an association between urbanization and distress by considering individual and environmental characteristics. The latter seem to explain the relationship between these concepts.     

1990－2010年中国人群伤害死亡率变化分析

目的 分析1990－2010年中国人群伤害死亡率的变化,为制订相关卫生政策和评价干预效果提供参考。方法 利用全球疾病负担2010课题组估算的中国伤害数据,采用线性回归模型分析1990－2010年中国不同人群伤害死亡率变化。结果 1990－2010年中国人群伤害死亡率总体呈下降趋势,下降幅度女性高于男性,0～4岁高于其他年龄段。2010年中国有79.6万人因伤害致死,年龄标准化死亡率为57/10万,其中各年龄段男性伤害死亡率均高于女性,≥70岁年龄段高于其他年龄段。在此期间,除道路交通伤害致死率显著上升外,其他类型伤害均有所下降。2010年伤害占中国总死亡人数的9.6%,超过传染性疾病、孕产妇、围产儿和营养性疾病的死亡数,伤害的主要类型是道路交通伤害、自我伤害、溺水和跌倒。同期,中国人群因主要危险因素所致的伤害死亡率也呈下降趋势,2010年伤害的前三位危险因素分别为职业性危险因素、酒精饮用和低骨密度(骨质疏松)。结论 1990－2010年中国人群伤害死亡率总体下降,但伤害仍是中国重要的公共卫生问题之一。     

Social work and toddler overweight risk: Identifying modifiable child and parent factors across the socioeconomic gradient

ABSTRACT

Objective: Childhood obesity is associated with long-term health consequences, yet little is known about the prevalence of child and parent risk factors of overweight across the socioeconomic gradient in early life. This exploratory study documents the prevalence of risk factors that contribute to overweight among toddlers within and across socioeconomic status (SES). Methods: Obesity risk factors were examined within and across SES quintiles in a nationally representative sample. Data were collected from 5,100 mothers and 2-year-old children. Weighted regression models assessed child and parent characteristics that predict toddler weight status in a national sample and samples stratified by SES quintiles. Results: Higher rates of overweight were observed in Q1 (29.2%) and reduced with each successive SES quintile (16.9%—Q5), suggesting a gradient effect. Results indicated factors unique within quintiles, distinct from the full national sample: Q1—motor development; Q2—motor and mental development, maternal BMI, breastfeeding, bottle feeding, introduction of solid foods; Q3—breastfeeding; and Q4–5—introduction of solid foods. Discussion: Findings further existing knowledge of toddler obesity by uncovering risks relevant for specific SES groups. Results yield implications for social workers to refine strategies for improving toddler health and preventing overweight/obesity.     

Socioeconomic status and non-fatal injuries among Canadian adolescents: variations across SES and injury measures

Background  

While research to date has consistently demonstrated that socioeconomic status (SES) is inversely associated with injury mortality in both children and adults, findings have been less consistent for non-fatal injuries. The literature addressing SES and injury morbidity among adolescents has been particularly inconclusive. To explore potential explanations for these discrepant research findings, this study uniquely compared the relationship across different measures of SES and different causes of injury (recreation versus non-recreation injuries) within a sample of Canadian adolescents.     

The Social Distribution of Health: Estimating Quality-Adjusted Life Expectancy in England

ObjectiveTo model the social distribution of quality-adjusted life expectancy (QALE) in England by combining survey data on health-related quality of life with administrative data on mortality.MethodsHealth Survey for England data sets for 2010, 2011, and 2012 were pooled (n = 35,062) and used to model health-related quality of life as a function of sex, age, and socioeconomic status (SES). Office for National Statistics mortality rates were used to construct life tables for age-sex-SES groups. These quality-of-life and length-of-life estimates were then combined to predict QALE as a function of these characteristics. Missing data were imputed, and Monte-Carlo simulation was used to estimate standard errors. Sensitivity analysis was conducted to explore alternative regression models and measures of SES.ResultsSocioeconomic inequality in QALE at birth was estimated at 11.87 quality-adjusted life-years (QALYs), with a sex difference of 1 QALY. When the socioeconomic-sex subgroups are ranked by QALE, a differential of 10.97 QALYs is found between the most and least healthy quintile groups. This differential can be broken down into a life expectancy difference of 7.28 years and a quality-of-life adjustment of 3.69 years.ConclusionsThe methods proposed in this article refine simple binary quality-adjustment measures such as the widely used disability-free life expectancy, providing a more accurate picture of overall health inequality in society than has hitherto been available. The predictions also lend themselves well to the task of evaluating the health inequality impact of interventions in the context of cost-effectiveness analysis.     

Are child pedestrians at increased risk of injury on one-way compared to two-way streets?

OBJECTIVES: To compare child pedestrian injury rates on one-way versus two-way streets in Hamilton, and examine whether the characteristics of child pedestrian injuries differ across street types. METHODS: The rates of injury per child population, per kilometre, per year were calculated by age, sex and socio-economic status (SES). Child, environment and driver characteristics were investigated by street type. RESULTS: The injury rate was 2.5 times higher on one-way streets than on two-way streets and 3 times higher for children from the poorest neighbourhoods than for those from wealthier neighbourhoods. SES, injury severity, number of lanes, collision location and type of traffic control were also found to be significantly different across street types. CONCLUSIONS: One-way streets have higher rates of child pedestrian injuries than two-way streets in this community. Future risk factor and intervention studies should include the directionality of streets to further investigate its contribution to child pedestrian injuries.     

Socio-economic risk factors for injuries in Swedish children and adolescents: A national study over 15 years

Abstract

Few studies have assessed if Sweden's injury prevention work has been equally effective for children of different socio-economic backgrounds. The goal of this paper is to review the country's injury rates for children over time, stratified by socio-economic status (SES), to see if the effects are similar across SES levels. This study employs a retrospective case-control study design, using data from the hospitalisation records of 51,225 children, which were linked to family socio-economic data. Children and adolescents in families receiving social welfare benefits, and those living with single parents and mothers with less education had higher risks of injuries leading to hospitalisation. The population-based safety work over the past decades seems to have had only minor effects on reducing the impact of socio-economic based difference in injury risks to younger Swedes.     

The 2011 and 2016 iterations of the Ontario Marginalization Index: updates,consistency and a cross-sectional study of health outcome associations

ObjectivesThe Ontario Marginalization Index (ON-Marg) is an area-based measure used widely to measure health inequalities in Ontario. Recently, the index was updated for 2011 and 2016. The loss of the 2011 long-form census required the use of alternative data sources for the 2011 version. This paper describes the update of ON-Marg, assesses consistency in the indices across census years using Dissemination Areas, and examines associations between ON-Marg 2016 and four health and social outcomes to demonstrate its potential to measure health inequalities.MethodsON-Marg was created using factor analysis. Differences in quintile assignment was compared over time to assess whether the use of taxfiler, immigration, property assessment, and health card address data in 2011 affected consistency in measurement of marginalization. Inequalities in rates of overall mortality, gonorrhea incidence, mental health emergency department visits, and alcohol retail locations across quintiles of ON-Marg 2016 were quantified using the Relative Index of Inequality.ResultsDepending on the dimension, between 81% and 96% of DAs showed limited or no changes in quintiles of marginalization between 2006, 2011 and 2016. Of the 45–64% of DAs that did not change quintile between 2006 and 2016, 1.8% to 8.8% of DAs in 2011 differed by two or more quintiles. Findings showed significant differences in rates of health and social outcomes across quintiles of ON-Marg 2016, with strength and directionality varying by dimension of ON-Marg.ConclusionAlternative data sources did not substantially affect the consistency of the 2011 version of ON-Marg. The updated ON-Marg is a comprehensive tool that can be used to study health inequalities in Ontario.     

State Firearm Legislation and Nonfatal Firearm Injuries

Objectives. We investigated whether stricter state-level firearm legislation was associated with lower hospital discharge rates for nonfatal firearm injuries.Methods. We estimated discharge rates for hospitalized and emergency department–treated nonfatal firearm injuries in 18 states in 2010 and used negative binomial regression to determine whether strength of state firearm legislation was independently associated with total nonfatal firearm injury discharge rates.Results. We identified 26 744 discharges for nonfatal firearm injuries. The overall age-adjusted discharge rate was 19.0 per 100 000 person-years (state range = 3.3–36.6), including 7.9 and 11.1 discharges per 100 000 for hospitalized and emergency department–treated injuries, respectively. In models adjusting for differences in state sociodemographic characteristics and economic conditions, states in the strictest tertile of legislative strength had lower discharge rates for total (incidence rate ratio [IRR] = 0.60; 95% confidence interval [CI] = 0.44, 0.82), assault-related (IRR = 0.58; 95% CI = 0.34, 0.99), self-inflicted (IRR = 0.18; 95% CI = 0.14, 0.24), and unintentional (IRR = 0.53; 95% CI = 0.34, 0.84) nonfatal firearm injuries.Conclusions. There is significant variation in state-level hospital discharge rates for nonfatal firearm injuries, and stricter state firearm legislation is associated with lower discharge rates for such injuries.Each year from 2005 to 2010, an average of 103 000 Americans were injured or killed by a firearm—approximately 282 individuals per day.1 Most public attention and research has focused on fatal firearm injuries because they are a leading cause of injury death and account for more than 30 000 deaths annually.1 Firearm injuries were the third leading cause of injury-related deaths in 2010 after poisoning and motor vehicle accidents and were the second most frequent cause of traumatic death related to a consumer product.1,2 However, a majority of firearm-related injuries in the United States are nonfatal.1,3,4 In 2010, nearly 5 individuals suffered nonfatal firearm injuries for every 2 who died as a result of firearm violence.1 The age-adjusted fatal firearm injury rate in that year was 10.1 per 100 000 person-years, less than half of the age-adjusted nonfatal injury rate (24.0 per 100 000 person-years).1 This high prevalence of nonfatal firearm injuries in the United States is associated with significant physical and psychological morbidity among injury survivors.5–7 It is also a substantial economic burden for victims, taxpayers, and the United States.8–12Numerous state and federal laws have been implemented in attempts to reduce firearm-related violence in the United States.13 Household firearm ownership rates have been shown to be associated with states’ rates of firearm-related suicides and homicides; thus, legislation might reduce firearm injuries by limiting overall firearm ownership.14,15 A strong association has also been demonstrated between safer firearm storage practices and a lower risk of suicide and unintentional firearm deaths.16–19 Hence, legislation aimed at increasing safe firearm storage may decrease firearm-related injuries, particularly in homes with children and adolescents. In addition, laws that promote background checks before firearm purchase and those that limit private firearm transactions and transfers may help limit firearm access by those most likely to harm themselves or others.Overall, the effectiveness of these laws individually or as a whole remains unclear. Two studies evaluated the relationship between state firearm legislation and firearm injuries using measures of state firearm legislation on the basis of annual scorecards created by the Brady Center to Prevent Gun Violence.20,21 These studies found lower rates of total firearm deaths, including homicides and suicides,20 as well as lower rates of firearm injuries in children,21 in states with more restrictive firearm legislation. Previous studies have also shown that laws related to background checks and limitations on handgun possession and transfer are associated with lower rates of firearm deaths, including suicides and homicides.22–25 A study of the 1994 Brady Handgun Violence Prevention Act (Pub L. No. 103-159, 107 Stat. 1536, USC 921–922, HR 1025, 103rd Congress), which established a mandatory waiting period and background check requirement for handgun sales through licensed firearm dealers, found that the law led to a decline in the suicide rate for those aged 55 years and older, although these findings may have been driven by the implementation of the waiting period rather than the background check itself.26Laws focused on preventing children’s access to firearms are associated with lower rates of both unintentional deaths and suicides.27,28 A cross-sectional, time series analysis of pooled data from 1979 to 2000 found that unintentional firearm deaths among children were declining nationally and that most states that enacted child access laws experienced greater declines in those injuries than did states that had not.29 Notably, state-level comparisons of child access laws can be driven largely by the few states with the strictest child access legislation (e.g., felony conviction for violations).29,30Additionally, several studies suggest that laws aimed at easing access to and use of firearms may be associated with higher rates of firearm injuries, including homicides.31–33 One study found that the 2007 repeal of Missouri’s permit to purchase law requiring firearm purchasers to obtain a license verifying that they passed a background check led to an increase in firearm-related homicides.33 Conversely, other studies have observed no association between stricter firearm laws and firearm violence,26,34,35 and a recent systematic review of various federal and state firearm laws found insufficient evidence to determine their effectiveness in reducing firearm-related violence and injuries.36Several studies have examined the relationship between firearm legislation and fatal firearm injuries, although little is known about the relationship between firearm legislation and nonfatal firearm outcomes.37 This relationship may differ from that observed with fatal injuries because of the different circumstances under which nonfatal firearm injuries occur, including differences in the age of the injured,1,3 the type of firearms involved,38 and injury intent.3 For instance, unintentional shootings are more likely to prove nonfatal than are intentional shootings, and a vast majority of self-inflicted injuries (i.e., suicide attempts) result in death.3,39 Because of the higher prevalence of nonfatal firearm injuries, studies of nonfatal injuries may also have greater statistical power to determine associations between legislation and firearm outcomes that might not be observed in studies of fatal injuries.We have described state variation in discharge rates for nonfatal firearm injuries in 2010 and determined whether stricter state-level firearm legislation was associated with lower discharge rates for nonfatal firearm injuries.     

The association between disability and unintentional injuries among adolescents in a general education setting: Evidence from a Swedish population-based school survey

BackgroundUnintentional injuries are the leading cause of death among adolescents. Adolescents with disabilities may be particularly vulnerable with an increased risk of unintentional injuries.ObjectiveTo study the association between a set of disabilities and unintentional injury risks among adolescents, accounting for comorbidity, subjective disability severity and sex.MethodCross-sectional data from a Swedish national school survey including 4,741 students (15 and 17-year olds) conducted in 2016 was analyzed using log-binomial generalized linear models.ResultsWe found a 33% increased risk of injury the last 12 months and a 53% increased risk of injury leading to hospitalization for adolescents with any disability compared to their peers with no disability. The differences in injury risk were greater for girls than boys. There was a dose-response relationship between disability severity and injury risk. In analyses adjusted for sociodemographic factors and comorbidity, attention-deficit/hyperactivity disorder (ADHD) and epilepsy were associated with an increased risk of injury the last 12 months, risk ratios [RR] were 1.41 (95% Confidence Interval [CI] 1.08–2.97) and 1.79 (95% CI 1.10–1.81) respectively. Autism spectrum disorder was associated with a decreased injury risk the last 12 months (RR = 0.43, CI 0.2–0.92). ADHD, mobility impairment and visual impairment were associated with hospitalization due to injury during lifetime.ConclusionsThere was an increased risk of unintentional injuries for adolescents with disabilities compared to their non-disabled peers, specifically for individuals with ADHD, epilepsy, visual impairment and mobility impairment. Injury prevention strategies may include adapting the physical environment and medical treatment.     

Racial and social class gradients in life expectancy in contemporary California

Life expectancy, or the estimated average age of death, is among the most basic measures of a population's health. However, monitoring differences in life expectancy among sociodemographically defined populations has been challenging, at least in the United States (US), because death certification does not include collection of markers of socioeconomic status (SES). In order to understand how SES and race/ethnicity independently and jointly affected overall health in a contemporary US population, we assigned a small-area-based measure of SES to all 689,036 deaths occurring in California during a three-year period (1999–2001) overlapping the most recent US census. Residence at death was geocoded to the smallest census area available (block group) and assigned to a quintile of a multifactorial SES index. We constructed life tables using mortality rates calculated by age, sex, race/ethnicity and neighborhood SES quintile, and produced corresponding life expectancy estimates. We found a 19.6 (±0.6) year gap in life expectancy between the sociodemographic groups with the longest life expectancy (highest SES quintile of Asian females; 84.9 years) and the shortest (lowest SES quintile of African–American males; 65.3 years). A positive SES gradient in life expectancy was observed among whites and African–Americans but not Hispanics or Asians. Age-specific mortality disparities varied among groups. Race/ethnicity and neighborhood SES had substantial and independent influences on life expectancy, underscoring the importance of monitoring health outcomes simultaneously by these factors. African–American males living in the poorest 20% of California neighborhoods had life expectancy comparable to that reported for males living in developing countries. Neighborhood SES represents a readily-available metric for ongoing surveillance of health disparities in the US.     

Social class and the occurrence of traffic injuries and deaths in urban children

This paper examines motor vehicle traffic accident deaths and injuries to pedestrians and bicyclists (ICD-9 codes E813-E814) aged 0-14 years, by income quintile of area of residence. It is based on 92 deaths in urban Canada in 1981, 69 deaths in Montreal during the period 1979-1983, and 1,133 injuries which resulted in hospital care or police reports in Montreal in 1981. For injuries in Montreal, the pattern of socio-economic inequality in the annual incidence rates by quintile was very pronounced, completely regular and highly significant. The rate of injury to children living in the poorest neighbourhoods was four times that of children living in the least poor neighbourhoods. For both sexes, inequalities were much more pronounced for pedestrians compared to bicyclists. For deaths in Montreal and all of urban Canada, the inequality in the rates did not follow such a consistent pattern across the income quintiles, nor were the differences statistically significant in most cases, but the rates for each sex were consistently highest in the poorest income quintile. Socio-economic inequalities in the rates of death and injury were greater in girls than in boys. The results are discussed in the context of theories of etiology and strategies for prevention.     

Post-tuberculosis mortality risk among immigrants to British Columbia,Canada, 1985–2015: a time-dependent Cox regression analysis of linked immigration,public health,and vital statistics data

ObjectiveTo compare non-tuberculosis (non-TB)-cause mortality risk overall and cause-specific mortality risks within the immigrant population of British Columbia (BC) with and without TB diagnosis through time-dependent Cox regressions.MethodsAll people immigrating to BC during 1985–2015 (N = 1,030,873) were included with n = 2435 TB patients, and the remaining as non-TB controls. Outcomes were time-to-mortality for all non-TB causes, respiratory diseases, cardiovascular diseases, cancers, and injuries/poisonings, and were ascertained using ICD-coded vital statistics data. Cox regressions were used, with a time-varying exposure variable for TB diagnosis.ResultsThe non-TB-cause mortality hazard ratio (HR) was 4.01 (95% CI 3.57–4.51) with covariate-adjusted HR of 1.69 (95% CI 1.50–1.91). Cause-specific covariate-adjusted mortality risk was elevated for respiratory diseases (aHR = 2.96; 95% CI 2.18–4.00), cardiovascular diseases (aHR = 1.63; 95% CI 1.32–2.02), cancers (aHR = 1.40; 95% CI 1.13–1.75), and injuries/poisonings (aHR = 1.85; 95% CI 1.25–2.72).ConclusionsIn any given year, if an immigrant to BC was diagnosed with TB, their risk of non-TB mortality was 69% higher than if they were not diagnosed with TB. Healthcare providers should consider multiple potential threats to the long-term health of TB patients during and after TB treatment. TB guidelines in high-income settings should address TB survivor health.Electronic supplementary materialThe online version of this article (10.17269/s41997-020-00345-y) contains supplementary material, which is available to authorized users.     

Injury Rate Comparisons for Nonmechanized and Mechanized Logging Operations,Washington State, 2005-2014

ABSTRACT

Objectives: Current industry classification systems in the United States do not differentiate mechanized and nonmechanized logging operations. The objectives of this article are to quantify injury risk differences between mechanized and nonmechanized logging operations in Washington State and to evaluate for potential injury risk tradeoffs, such as decreasing traumatic injuries while increasing nontraumatic injuries that might occur when mechanized logging operations are substituted for nonmechanized logging operations.

Methods: Using Washington State workers’ compensation insurance risk classes to differentiate mechanized and nonmechanized logging operations, injury and illness claims data and employer reported hours were used to compare claim rates and to characterize injuries by type of logging operation.

Results: From 2005 to 2014, the accepted Washington State worker’s compensation claim rate for nonmechanized logging was 46.4 per 100 full-time equivalent employees compared to 6.7 per 100 full-time equivalent (FTE) for mechanized logging activities. The rate ratio for comparing nonmechanized to mechanized logging claims rates for all accepted claims was 6.9 (95% Confidence Interval 6.4–7.5). Claim rates for traumatic injury and nontraumatic injuries in nonmechanized logging exceeded comparable rates in mechanized logging activities, although the distribution of types of injury differed by type of logging operation. A greater percentage of accepted claims in nonmechanized logging were traumatic injuries than in mechanized logging (92.2% vs. 85.0%, respectively). In addition, nonmechanized logging had higher total claim and medical costs per FTE and had a higher proportion of claims with lost work time than mechanized logging.

Conclusion: Mechanized logging offers a considerable safety advantage over nonmechanized logging operations. Continued efforts to increase the mechanization of logging operations will result in decreased injury rates.     

Socioeconomic Status and Bullying: A Meta-Analysis

We examined whether socioeconomic status (SES) could be used to identify which schools or children are at greatest risk of bullying, which can adversely affect children’s health and life.We conducted a review of published literature on school bullying and SES. We identified 28 studies that reported an association between roles in school bullying (victim, bully, and bully-victim) and measures of SES. Random effects models showed SES was weakly related to bullying roles. Adjusting for publication bias, victims (odds ratio [OR] = 1.40; 95% confidence interval [CI] = 1.24, 1.58) and bully-victims (OR = 1.54; 95% CI = 1.36, 1.74) were more likely to come from low socioeconomic households. Bullies (OR = 0.98; 95% CI = 0.97, 0.99) and victims (OR = 0.95; 95% CI = 0.94, 0.97) were slightly less likely to come from high socioeconomic backgrounds.SES provides little guidance for targeted intervention, and all schools and children, not just those with more socioeconomic deprivation, should be targeted to reduce the adverse effects of bullying.Bullying is defined as repeated, harmful behavior, characterized by an imbalance of power between the victim and perpetrator(s).1 There is compelling evidence that school bullying affects children’s health and well being, with the effects lasting long into adulthood.2,3 Victims of school bullying are at greater risk of physical and mental health problems,4,5 including depression,6,7 anxiety,8,9 psychotic or borderline personality symptoms,10,11 and are more likely to self-harm and attempt suicide.12,13 A small proportion of victims are classified as bully-victims, children who are victimized by their peers, but who also bully other children. Bully-victims are at even greater risk for maladjustment,5 exhibiting attention and behavioral difficulties,4,14 displaying poor social skills,15,16 and reporting increased levels of depression and anxiety through adolescence and into adulthood.2 By contrast, the negative outcomes of bullying perpetration are less clear. Bullies have been found more likely to engage in delinquent or antisocial behavior17,18; however, once other family and childhood risk factors are taken into account, they do not appear to be at any greater risk for poorer health, criminal, or social outcomes in adulthood.3Up to one third of children are involved in bullying, as bully, victim, or bully-victim,19,20 and when considered alongside the damaging effects on physical and mental health, bullying can be seen as a major public health concern.21 Identifying risk factors for bullying aids potential efforts in targeting resources, which can prevent youths from becoming involved in bullying, but also limits the impact it has on their health and well being. Traditional risk factors, such as age and gender, show a clear association22,23; however, there are a range of other potential determinants whose relationship to bullying remain unclear. One such determinant is socioeconomic status (SES), which shows some links to bullying, but at present, research findings are inconsistent regarding roles (i.e., bully, victim, or bully-victim).SES is an aggregate concept comprising resource-based (i.e., material and social resources) and prestige-based (individual’s rank or status) indicators of socioeconomic position, which can be measured across societal levels (individual, household, and neighborhood) and at different periods in time.24 It can be assessed through individual measures, such as education, income, or occupation,25,26 but also through composite measures that combine or assign weights to different socioeconomic aspects to provide an overall index of socioeconomic level. There is no standard measure of SES; indicators are used to measure specific aspects of socioeconomic stratification.26 Accordingly, different measures of SES may show varying effects, which can result from differing causal pathways, or through interactions with other social characteristics, such as gender or race.27 The multifaceted nature of SES has resulted in a lack of consistency in how researchers measure its relationship to bullying, and although several studies provide individual assessments of this relationship, as yet there is no clear consensus over whether roles in bullying are associated with individual socioeconomic measures, or in general, with SES.Currently, the literature suggests some link between low SES and victims or bully-victims at school.28,29 Specifically, being a victim has been reported to be associated with poor parental education,30,31 low parental occupation,32 economic disadvantage,33,34 and poverty.35 In addition, several studies found that bully-victims are also more likely to come from low socioeconomic backgrounds,29,30 including low maternal education28 and maternal unemployment.36 However, others found little or no association between SES and victims or bully-victims.37–39 The type of bullying may matter in relation to SES. Victims of physical and relational bullying have been found to more often come from low affluence families, whereas victims of cyber bullying have not.40Compared with victimization, few studies have explored the link between SES and bullying others. Some studies found bullying others to be associated with low SES, including economic disadvantage,34 poverty,35 and low parental education.30 Additionally, where composite measures have been used, children from low socioeconomic backgrounds have been found to bully others slightly more often.29,41 By contrast, others found no association between bullying perpetration and measures of SES.38,39,42There is a small but growing body of literature that examines the relationship between bullying and SES, and although findings tend to suggest that victims, bully-victims, and bullies are more likely to come from low socioeconomic backgrounds, the results are far from conclusive. First, studies differ in their approach to measuring SES; some use composite measures, combining multiple indicators such as parental education, wealth, and occupation, whereas others concentrate on a single socioeconomic indicator, most often parental education, affluence, or occupation. How bullying relates to SES may differ according to which socioeconomic indicator is used; therefore, in interpreting results, one must consider not only how bullying relates to SES in general, but also which socioeconomic indicator was used, and how this may have influenced the result. Furthermore, although several studies indicate an association between bullying and low SES, the reported effect sizes vary greatly across studies, with some reporting weak and others moderate to strong associations. So far, the associations between bullying and SES have not been quantified across a range of studies in a systematic way. To address this gap in the literature, we conducted a systematic review and meta-analysis that aimed to determine more precisely the exact nature and strength of the relationship between SES and bullying. We systematically investigated the association between the role taken in school bullying (victim, bully, or bully-victim) and measures of SES.