Abstract
Purpose
Studies have found that many people who sustain an injury can experience adverse outcomes for a considerable time thereafter. Māori, the Indigenous peoples of Aotearoa me Te Waipounamu (New Zealand; NZ), are no exception. The Prospective Outcomes of Injury Study (POIS) found that almost three-quarters of Māori participants were experiencing at least one of a range of poor outcomes at two years post-injury. The aim of this paper was to estimate the prevalence, and identify predictors, of adverse health-related quality of life (HRQoL) outcomes in the POIS-10 Māori cohort, 12 years after participants sustained an injury.
Methods
Interviewers reached 354 individuals who were eligible to participate in a POIS-10 Māori interview, to be conducted a decade after the last phase of POIS interviews (held 24 months post-injury). The outcomes of interest were responses to each of the five EQ-5D-5L dimensions at 12 years post-injury. Potential predictors (i.e., pre-injury sociodemographic and health measures; injury-related factors) were collected from earlier POIS interviews. Additional injury-related information was collected from administrative datasets proximate to the injury event 12 years prior.
Results
Predictors of 12-year HRQoL outcomes varied by EQ-5D-5L dimension. The most common predictors across dimensions were pre-injury chronic conditions and pre-injury living arrangements.
Conclusion
An approach to rehabilitation where health services proactively enquire about, and consider the broader aspects of, patient health and wellbeing throughout the injury recovery process, and effectively coordinate their patients’ care with other health and social services where necessary, may help improve long-term HRQoL outcomes for injured Māori.
Similar content being viewed by others
Avoid common mistakes on your manuscript.
Introduction
The Prospective Outcomes of Injury Study (POIS) is a cohort study of 2856 New Zealanders aged 18–64 years when injured between 2007 and 2009 [1]. Participants experienced a range of injury types and severities (e.g. 25% were hospitalised for their injury), and POIS obtained extensive information about pre-injury, injury-related and post-injury factors from interviews at 3, 12 and 24 months (on average) post-injury [1, 2]. Data collection for POIS-10 Māori [2], a 12-year follow-up of Māori POIS participants, was completed in July 2021.
A specific aim of POIS has been to provide findings of high relevance and utility to Māori [3]. Like many Indigenous populations, Māori experience significant health and well-being inequities, including inequities in adverse injury outcomes compared to non-Māori [4,5,6]. Our previous analyses found a substantial proportion of the Māori cohort experienced adverse outcomes to 24 months following their ‘sentinel’ injury (i.e., the injury which led them to being recruited to POIS). Using the EQ-5D-3L [7], 55% experienced pain or discomfort 12 months post-injury, 33% had difficulty performing usual activities, and 21% experienced anxiety or depression [8]. Pre-injury prevalence for these was 10%, 5%, and 6%, respectively. At 24 months post-injury, 19% reported disability (WHODAS ≥ 10) compared to 9% pre-injury [9]. Overall, nearly three-quarters (72%) of Māori participants reported ≥ 1 adverse outcome at the 24-month interview (e.g. poorer health-related quality of life (HRQoL), disability, or not returning to paid employment) [2].
While evidence of adverse injury outcomes persisting well beyond two years is increasing [10], much of it comes from studies focussing on specific populations [11], injury types [12, 13], or injuries categorised as serious [14,15,16,17,18,19,20,21,22]. A paucity of research with general populations whose injuries vary in type and severity remains. It is vital we understand the longer-term impacts of injuries classed as ‘minor’ as these comprise the majority of injuries, contributing to over two-thirds of years lived with injury-induced disability [23, 24]. Likewise, very little beyond our own work is known about Indigenous injury outcomes, especially long-term. The aim of this paper is to estimate the prevalence, and identify predictors, of problems with HRQoL 12 years post-injury in the POIS-10 Māori cohort.
Methods
Detailed information on recruitment and data collection for POIS and POIS-10 Māori is available elsewhere [2, 25]. Briefly, individuals from one of five regions of Aotearoa me Te Waipounamu (NZ), aged 18–64 years when sustaining an injury resulting in an Accident Compensation Corporation (ACC) entitlement claim, were invited to participate. ACC is NZ’s universal no-fault injury insurer, and entitlement claimants are those who qualify for earnings-related compensation, rehabilitation costs, or additional support for their injury [26].
Interviews collected socio-demographic, health and wellbeing, and injury-related information from participants up to 12 years post-injury. Injury-related information was also collected from ACC claims data and hospital discharge data from the Ministry of Health’s National Minimum Dataset (NMDS). The NZ Health and Disability Multi-region Ethics Committee granted the study ethical approval (MEC/07/07/093/AM07).
Outcomes of interest were the five dimensions of the EQ-5D-5L [27] (i.e., mobility, self-care, usual activities, pain/discomfort, anxiety/depression), dichotomised (in order to facilitate comparison of our 12-year findings with our earlier HRQoL findings measured using the EQ-5D-3L) into ‘problems’ (slight, moderate, severe or extreme problems) and ‘no problems’. Bivariate analyses tested the association between each outcome and a range of pre-injury sociodemographic, health and sentinel injury-related characteristics (Table 1). Potential predictors of 12-year EQ-5D-5L outcomes were selected based on relevant injury and Māori health literature (e.g. [28,29,30],) and previous POIS findings [8, 31,32,33].
Bivariate analyses were used to construct a multivariable model for the five outcomes. Potential predictors were included if the p-value from its bivariate test of association was < 0.2. These models were subjected to a stepwise backwards elimination regression analysis [34]. Variables were retained if their associated p-value was < 0.15. Gender, age, injury severity (New Injury Severity Score; NISS) [35], pre-injury EQ-5D-3L dimension status, and days from injury to 12-year interview were forced into each model. Modified Poisson regression was used to estimate the relative risk and confidence interval for each retained variable using robust error variances [36]. Analyses were conducted using Stata/SE 13.1 [37].
Results
A total of 521 potential participants met the eligibility criteria for POIS-10 Māori. Upon contacting potential participants, 12 were found to have died. This left 509 potential interviewees of whom 354 were successfully contacted and 305 completed an interview.
HRQoL outcomes 12 years post-injury
One-third (34%) of the cohort were experiencing problems with mobility 12 years post-injury and 20% were having self-care difficulties. Problems performing usual activities were experienced by 30%, and 60% were having problems with pain/discomfort. More than one-quarter (29%) were experiencing anxiety/depression.
Potential predictors of HRQoL outcomes at 12 years post-injury
Table 2 presents the results of our bivariate analyses. Potential predictor variables included in the multivariable models are those where the resulting p-value was < 0.2 (underlined).
Predictors of HRQoL outcomes at 12 years post-injury
Mobility
Four of eight variables retained in the multivariable model were found to have a statistically significant association with mobility problems at 12 years post-injury (Table 3). Those aged 30–44 years when injured were almost twice as likely to be experiencing mobility problems than those aged 18–29 years. The risk of problems was also higher among those who had ≥ 2 chronic conditions compared to those who had none. Participants with a hazardous drinking pattern in the year before injury, and those living with others (family/non-family), were at lower risk of experiencing mobility problems.
Self-care
Ten variables were retained in the multivariable model for self-care; six were associated with the outcome (Table 3). Those aged 30–44 years when injured were at greater risk of self-care problems 12 years post-injury than those aged 18–29 years. Also at greater risk were those with self-care problems pre-injury and those with ≥ 2 chronic conditions compared to those with none. Participants with a hazardous drinking pattern, those living with others when injured, and those engaging in moderate to vigorous physical activity ≥ 5 days a week prior to their sentinel injury, were at lower risk of self-care problems.
Usual activities
Four of eight variables retained in the usual activities multivariable model had a statistically significant association with the outcome (Table 3). Participants aged ≥ 30 years at the time of their injury were more likely to experience problems 12 years post-injury than those who were younger. Those with ≥ 2 chronic conditions were also more likely to be having problems than those with no chronic conditions. At lower risk of problems were those living with family members at the time of their injury compared to those living alone, and those who were hospitalised for their injury compared to those who were not.
Pain/discomfort
Four of nine retained variables had a statistically significant association with pain/discomfort at 12 years post-injury (Table 3). Those experiencing pain/discomfort prior to their injury were 1.4 times more likely than those who were not to be experiencing pain/discomfort at 12 years. At higher risk also were those who had trouble accessing health services for their injury compared to those who did not, and those with a BMI ≥ 30 compared to those with a lower BMI. Those living with their family when injured were less likely than those living alone to be having problems with pain/discomfort at 12 years.
Anxiety/depression
Ten variables were retained in the multivariable model for anxiety/depression; six had a statistically significant association with the outcome (Table 3). Participants whose injury was of moderate severity were at 1.7 times higher risk of anxiety/depression 12 years post-injury than those whose injury was of low severity, and those with ≥ 2 chronic conditions were around twice as likely to be experiencing anxiety/depression than individuals with only one (RR: 1.75; 95% CI 1.13, 2.71) or no chronic conditions. Individuals who perceived their injury to be a threat to their life were more likely to be experiencing anxiety/depression 12 year later than those who did not, while those hospitalised for injury were at lower risk than those not hospitalised. At lower risk of anxiety/depression were participants whose pre-injury household income was deemed adequate and those satisfied with their social relationships pre-injury.
Discussion
The prevalence of HRQoL problems 12 years post-injury in the POIS-10 Māori cohort ranged from 20% for self-care to 60% for pain/discomfort. Estimates were lower than at 3 months post-injury (except for anxiety/depression) [31] but higher than the 12-month estimates (except for usual activities) [8]. Increases from 12 months post-injury are likely to be due, at least in part, to the increasing age of the cohort. Compared to the NZ population aged 25 and over, the POIS-10 Māori cohort had a slightly higher prevalence of mobility problems (30% v. 34%), greater problems with self-care (9% v. 20%), the same prevalence of problems with usual activities (both 30%), slightly lower prevalence of pain/discomfort (63% v. 60%), and a lower prevalence of anxiety/depression (44% v. 29%) [50]. Population norms specifically for Māori are not yet available.
The most common predictors for 12-year HRQoL outcomes were pre-injury chronic conditions (mobility, self-care, usual activities and anxiety/depression) and living arrangements (mobility, self-care, usual activities, pain/discomfort). Individuals who had ≥ 2 chronic conditions at the time of their injury were at greater risk of problems than those with none. This was the case for only usual activities and anxiety/depression at 12-months post-injury [51]. It may be that the burden of chronic conditions is now resulting in problems with mobility and self-care also, either through affecting recovery or simply via the cumulative impact of these conditions over time. Living arrangements, on the other hand, did not predict any HRQoL problems at 12 months post-injury [51] whereas those living with other people, in particular family members, prior to their injury were at lower risk of HRQoL problems at 12 years. It could be that this is a marker for the strength of peoples’ support networks and that those with greater support are less likely to encounter HRQoL problems, as has been found elsewhere (e.g., [52]).
Satisfaction with social relationships pre-injury protected against the only 12-year outcome that living situation did not, i.e., anxiety/depression. This may reflect individuals’ feelings of isolation as much as support in overcoming any long-term consequences of their POIS injury. Previous research has found perceived loneliness [53] and social interaction frequency [54, 55] to be associated with mental wellbeing and depression in older adults. At 12 months post-injury, pre-injury satisfaction with social relationships only protected against problems with self-care. We suggested these support networks may help individuals recover from injury but advised treating the finding with caution given there were only a small number of participants experiencing problems with self-care at 12 months [51]. It is also possible, however, that attrition at 12 years is the reason why satisfaction with social relationships did not protect against problems with self-care.
Another variable that predicted problems with self-care at 12 months, but not 12 years, was pre-injury BMI. It instead predicted problems with pain/discomfort. Those with a pre-injury BMI ≥ 30 were at greater risk of pain/discomfort than those with a BMI < 30. While we recommended treating findings regarding 12-month predictors of self-care problems with caution [51], BMI also predicted 12-month problems with self-care in the total cohort [56]. Previous studies have found an association between obesity and pain [57, 58] and future problems with pain [59,60,61]. Evidence also suggests that obesity increases the risk of injury [62, 63], particular patterns of injury [64], and adverse injury outcomes [62, 65]. The greater risk of pain/discomfort at 12 years in those with a higher pre-injury BMI may be due to the impacts of obesity, either alone or in exacerbating pain/discomfort associated with the sentinel injury.
Adequacy of household income, on the other hand, no longer predicted problems with pain/discomfort at 12 years after being found to protect against it at 12 months. We surmised that adequate household income may have afforded this group better access to medicinal treatments that relieved pain/discomfort. Having adequate household income pre-injury protected against anxiety/depression at 12 years post-injury. While it is possible that more disposable income has enabled better access to support and services, it is perhaps more likely that the observed changes are due to the association between financial security and anxiety/depression [66]. This relationship may have become more pronounced as the cohort has aged towards retirement. It is less clear why pre-injury income adequacy no longer protects against pain/discomfort.
Those aged 18–29 years at the time of their injury were less likely to be experiencing problems with mobility, self-care and usual activities at 12 years than those who were older. Notably, those aged 30–44 years when injured tended to have higher risk estimates than those aged 45–64 years. This may be an artefact of having missing information for those in the oldest age group who had relatively poorer health. They could have been lost-to-follow-up at a greater rate than those in the oldest age group with relatively better health due to having passed away [67] or because they were too unwell for interview, thereby biasing the relative risk estimates downwards. The highest risk of HRQoL problems at 12 months was in the 45–64 year-old age group, although the only statistically significant association was with mobility [51].
Gender predicted problems with usual activities, pain/discomfort and anxiety/depression at 12 months but not at 12 years. We could not think of a reason why females were at higher risk of problems at 12 months post-injury nor is it clear why females are no longer at higher risk, but attrition is one possibility if less healthy females were more likely to be lost-to-follow-up at 12 years. Another potential explanation is reporting bias if males were more likely to downplay HRQoL problems at 12 months post-injury compared to females. Perceiving one’s injury as a threat of longer-term disability at the time of the sentinel injury event also failed to predict any 12-year outcomes after predicting problems with mobility, usual activities and pain/discomfort at 12 months (and being retained in the models for self-care and anxiety/depression). This could be due to the impact of participants’ sentinel injuries now being less pronounced and no longer significantly impacting on HRQoL outcomes.
One new predictor at 12 years was perceived threat to life; those who felt their injury was a threat to their life at the time of the sentinel injury event were at higher risk of anxiety/depression. The emotional impact of injury may have been greater and longer lasting among this group than in those who only perceived a threat of disability. This is consistent with injury severity, as measured by NISS, which also predicted problems with anxiety/depression at 12 years after predicting no outcome at 12 months. These findings are partially supported by previous studies, although comparisons are difficult given the dearth of research examining injury outcomes beyond two years. Brasel et al. (2010) [68] found hospitalised patients’ perceived injury severity to predict mental health status six months later—greater perceived injury severity was associated with poorer mental quality of life. Perceived severity was not associated with clinical severity scores [68] which have been found to have no association with psychological distress up to 24 months post-injury [69, 70].
Those experiencing difficulties with mobility, self-care or anxiety/depression prior to their injury were more likely to be experiencing difficulties with the corresponding outcome at 12 months. However, the only statistically significant association was between pre-injury problems with self-care and 12-month problems with self-care. Conversely, pre-injury pain/discomfort predicted pain/discomfort at 12 years after having no association with pain/discomfort at 12 months. Reasons for these differences are unclear. Mobility problems and anxiety/depression due to the cohorts’ increasing age and/or other significant events post-injury may have disproportionately increased in the group who had no pre-injury problems with these outcomes. Alternatively, those who had problems with these outcomes pre-injury may have actively sought treatment for them over the past 12 years or otherwise reached a point where they no longer consider these a problem. These scenarios would diminish the relative risk of these problems at 12 years between the two groups (i.e., those with and those without these problems pre-injury), and may have occurred to a greater extent for mobility and anxiety/depression than for self-care. Indeed, evidence shows mobility problems are associated with anxiety/depression [71]. Combined with lower statistical power at 12 years relative to the 12-month analyses, this may explain why pre-injury mobility and anxiety/depression problems were not statistically significant predictors at 12 years.
The 12-year finding for pre-injury pain/discomfort seemingly contradicts the finding for pre-injury mobility. An intuitive reason for increasing mobility problems is increased pain/discomfort but several factors can lead to mobility problems, including neurological and cardiovascular conditions [71]. The sentinel injury may have been the cause for much pain/discomfort throughout the cohort at 12 months such that pre-injury pain/discomfort was not a predominant factor in the outcome. Pre-injury pain/discomfort could be a predictor of the outcome at 12 years because much of the pain/discomfort attributable to the sentinel injury may have diminished. Pre-injury pain/discomfort could be a marker for those with long-term chronic pain or those more sensitive to pain [72].
Occupation (self-care), prior injury (pain/discomfort) and recreational drug use (anxiety/depression) were retained in the 12-year multivariable models for the same outcomes they predicted at 12 months but were no longer statistically significant. Potential reasons for this include attrition and lower statistical power for 12-year analyses compared to 12-month analyses.
New predictors at 12 years post-injury were physical activity, hospitalisation, and drinking behaviour. Participants who were exercising 5–7 days a week prior to injury were less likely that those exercising < 5 days to experience difficulties with self-care. The benefits of regular exercise on physical and mental health are well established [73], and evidence suggests it can have a positive effect on health outcomes long-term [74]. Perhaps our finding reflects this, and, in future, physical exercise will show protection against problems with the other HRQoL outcomes as well.
Those hospitalised because of their sentinel injury were less likely to be experiencing problems with usual activities and anxiety/depression. Hospitalised participants possibly received better rehabilitation and care compared to those not hospitalised. This is consistent with our finding for those who had trouble accessing health services for their injury. They were at higher risk of pain/discomfort at 12 years post-injury, perhaps due to insufficient treatment for their injury. Unlike at 12 months, trouble accessing health services did not predict problems with usual activities and anxiety/depression at 12 years. Perhaps those who did have trouble accessing health services for their injury have since recovered to the point where they are no longer emotionally affected by their injury and have been able to resume their usual activities (or at least what they now define as their usual activities) but still experience pain/discomfort that has largely alleviated among those who did not have trouble.
Pre-injury drinking behaviour, like hospitalisation, also had a protective effect for two outcomes. Those classified as hazardous drinkers (i.e., consuming alcohol in a pattern that “increases the risk of harmful consequences for the user or others” [75]) were less likely to be experiencing problems with mobility and self-care at 12 years than those who were not. We cannot think of any plausible reason why hazardous drinking would have a protective effect on these outcomes. The AUDIT-C (range 0–12) [47] was used to measure drinking behaviour. Females who scored ≥ 3 and males who scored ≥ 4 were classified as hazardous drinkers. Studies have found variation in optimal AUDIT-C cut-off points across different populations [76] and it is possible ours were too low.
The finding of a protective effect is somewhat consistent with the “J-shaped alcohol-health curve” observed in several studies examining alcohol consumption and health outcomes [77]. Perhaps we would have observed something similar had we used more than two categories of hazardous drinking (e.g., no/low, moderate, high). Even so, more recent epidemiological evidence shows that the J-shaped alcohol-health curve is highly likely to be an artefact of study design. Purported health benefits of low to moderate alcohol consumption are increasingly doubtful, and it is more likely that alcohol consumption is a marker of better health rather than a cause of it [77, 78]. That may be what we are observing here, and although we adjusted for pre-injury chronic conditions and HRQoL status, hazardous drinking may be capturing another dimension of health. Drinking behaviour can also vary throughout life [79] and we do not know how subsequent drinking behaviour in the intervening years may be impacting on 12-year outcomes.
This is one of only a small number of studies to have examined HRQoL outcomes beyond two years in a general population cohort of injured individuals. Even fewer studies have focussed on a cohort whose injuries varied in type and severity and where most were not hospitalised because of their injury. It is the only study we are aware of that has examined long-term HRQoL outcomes specifically in an injured Indigenous cohort and it is a strength that we have been able to follow-up over half of the sizeable Māori cohort to 12 years post-injury. Nonetheless, our analyses and the statistical precision of our estimates have been restricted by relatively limited statistical power. Consequently, there may be predictors of 12-year HRQoL outcomes that our analyses have not revealed. We used the scientific literature, including our own previous findings, to select variables for our analyses and to inform the regression models. This was done in an effort to overcome the limitations of stepwise regression [80], ensuring our final models were not simply produced by subjecting numerous variables to this method and reducing the chance of extraneous variables being identified as predictors.
The potential for attrition to be influencing our findings is considerable, at least in comparison to our 12-month findings [51, 81]. This may be biasing our observed estimates and limiting the generalisability of our findings. An analysis of non-participation at 12 years post-injury would provide more insight into this. Other potential limitations are likely to be having little impact on our findings. Considerable effort was made to address response error by reassuring participants that taking part in the study would not affect their healthcare or injury compensation in any way. It was highlighted that POIS was being conducted independent of ACC and no individual data was being shared with the organisation. Earlier POIS analyses suggest that any bias from recalled pre-injury health information, collected from participants three months (on average) after their injury, is also likely to be minimal [82].
We made a deliberate decision to focus on pre-injury and injury-related predictors to inform policy, decision-making and practice early on in people’s recovery pathway that may prevent long-term HRQoL problems. A limitation of this is that we do not know what influence behaviour and events in the years since is having on 12-year outcomes. POIS-10 Māori has collected information on major life events, changes in employment, and changes in health in the decade since the 24-month post-injury interview [2]. Findings from this study will help inform future POIS analyses utilising longitudinal data that examine the impact of post-injury factors on 12-year outcomes.
Our findings support a proactive, holistic, integrated approach to the rehabilitation of entitlement claimants. Claimants’ overall health and wellbeing, including comorbidities, living arrangements and social supports should be considered as part of their injury treatment plan. This could, for example, include a focus on the benefits of developing and sustaining a routine of regular physical activity and, if necessary, reducing one’s BMI to improve future HRQoL outcomes. Attention should be paid to an individual’s perceived severity of their injury, particularly in relation to their mental wellbeing. There may well be benefit in proactively following-up with injured patients, particularly those not hospitalised for their injury and/or who are living alone, to see how their recovery is progressing, how they are coping, directing them to any support they may be eligible for and would likely benefit from, and providing advice on further actions they could take to optimise their recovery and HRQoL. Having a process to ensure effective coordination for claimants between the necessary health and social services to optimise their HRQoL outcomes would be particularly useful. Findings from previous research (e.g., [28, 83]) highlight the importance of culturally safe health services for Māori that are easily accessible in order to facilitate obtaining appropriate treatment for injury and other health and wellbeing concerns.
Data availability
The study data cannot be shared due to ethical constraints.
Code availability
Code for the statistical analyses is available from the corresponding author upon reasonable request.
References
Derrett, S., Wyeth, E. H., Richardson, A., Davie, G., Samaranayaka, A., Lilley, R., & Harcombe, H. (2021). Prospective outcomes of injury study 10 years on (POIS-10): An observational cohort study. Methods and Protocols, 4(2), 35.
Wyeth, E. H., Derrett, S., Nelson, V., Bourke, J., Crengle, S., Davie, G., & Harcombe, H. (2021). POIS-10 Māori: Outcomes and experiences in the decade following injury. Methods and Protocols, 4(2), 37.
Wyeth, E. H., Derrett, S., Hokowhitu, B., Hall, C., & Langley, J. (2010). Rangatiratanga and Oritetanga: Responses to the treaty of Waitangi in a New Zealand study. Ethnicity & Health, 15(3), 303–316.
Ministry of Health and the Accident Compensation Corporation. (2013). Injury-related health loss: A report from the New Zealand Burden of Diseases, Injuries and Risk Factors Study 2006–2016. Ministry of Health.
Ministry of Health. (2015). Tatau Kahukura: Māori health chart book 2015 (3rd ed.). Ministry of Health.
Statistics New Zealand. (2015). He hauā Māori: Findings from the 2013 disability survey. Statistics New Zealand.
EuroQol Group. (2013). EQ-5D-3L | About. Retrieved August 30, 2021, from https://euroqol.org/eq-5d-instruments/eq-5d-3l-about/
Maclennan, B., Wyeth, E., Davie, G., Wilson, S., & Derrett, S. (2014). Twelve-month post-injury outcomes for Māori and non-Māori: Findings from a New Zealand cohort study. Australian and New Zealand Journal of Public Health, 38(3), 227–233.
Wyeth, E. H., Samaranayaka, A., Davie, G., & Derrett, S. (2017). Prevalence and predictors of disability for Māori 24 months after injury. Australian and New Zealand Journal of Public Health, 41(3), 262–268.
Geraerds, A. J. L. M., Richardson, A., Haagsma, J., Derrett, S., & Polinder, S. (2020). A systematic review of studies measuring health-related quality of life of general injury populations: update 2010–2018. Health and Quality of Life Outcomes, 18(1), 160.
Yiengprugsawan, V., Berecki-Gisolf, J., McClure, R., Kelly, M., Seubsman, S.-a, Sleigh, A. C., the Thai Cohort Study T. (2014). The effect of injuries on health measured by short form 8 among a large cohort of thai adults. PLoS ONE, 9(2), e88903.
Grauwmeijer, E., Heijenbrok-Kal, M. H., Haitsma, I. K., & Ribbers, G. M. (2017). Employment outcome ten years after moderate to severe traumatic brain injury: A prospective cohort study. Journal of Neurotrauma, 34(17), 2575–2581.
Theadom, A., Starkey, N., Barker-Collo, S., Jones, K., Ameratunga, S., & Feigin, V. (2018). Population-based cohort study of the impacts of mild traumatic brain injury in adults four years post-injury. PLoS ONE, 13(1), e0191655.
Ballantyne, P. J., Casey, R., O’Hagan, F. T., & Vienneau, P. (2016). Poverty status of worker compensation claimants with permanent impairments. Critical Public Health, 26(2), 173–190.
Casey, R., & Ballantyne, P. J. (2017). Diagnosed chronic health conditions among injured workers with permanent impairments and the general population. Journal of Occupational and Environmental Medicine, 59(5), 486–496.
Gabbe, B. J., Simpson, P. M., Cameron, P. A., Ponsford, J., Lyons, R. A., Collie, A., Fitzgerald, M., Judson, R., Teague, W. J., Braaf, S., Nunn, A., Ameratunga, S., & Harrison, J. E. (2017). Long-term health status and trajectories of seriously injured patients: A population-based longitudinal study. PLoS Medicine, 14(7), e1002322.
Gross, T., Schuepp, M., Attenberger, C., Pargger, H., & Amsler, F. (2012). Outcome in polytraumatized patients with and without brain injury. Acta Anaesthesiologica Scandinavica, 56(9), 1163–1174.
O’Hagan, F. T., Ballantyne, P. J., & Vienneau, P. (2012). Mental health status of Ontario injured workers with permanent impairments. Canadian Journal of Public Health, 103(4), 303–308.
Ringdal, M., Plos, K., Örtenwall, P., & Bergbom, I. (2010). Memories and health-related quality of life after intensive care: A follow-up study*. Critical Care Medicine, 38(1), 38–44.
Soberg, H. L., Bautz-Holter, E., Finset, A., Roise, O., & Andelic, N. (2015). Physical and mental health 10 years after multiple trauma: A prospective cohort study. Journal of Trauma and Acute Care Surgery, 78(3), 628–633.
Soberg, H. L., Finset, A., Roise, O., & Bautz-Holter, E. (2012). The trajectory of physical and mental health from injury to 5 years after multiple trauma: A prospective, longitudinal cohort study. Archives of Physical Medicine and Rehabilitation, 93(5), 765–774.
Spittal, M. J., Grant, G., O’Donnell, M., McFarlane, A. C., & Studdert, D. M. (2018). Development of prediction models of stress and long-term disability among claimants to injury compensation systems: A cohort study. British Medical Journal Open, 8(4), e020803.
Lyons, R. A., Kendrick, D., Towner, E. M., Christie, N., Macey, S., Coupland, C., Gabbe, B. J., on behalf of the UKBoISG. (2011). Measuring the population burden of injuries—implications for global and national estimates: A Multi-centre prospective UK longitudinal study. PLoS Medicine, 8(12), e1001140.
Polinder, S., Haagsma, J. A., Toet, H., & van Beeck, E. F. (2012). Epidemiological burden of minor, major and fatal trauma in a national injury pyramid. The British Journal of Surgery, 99(Suppl 1), 114–121.
Derrett, S., Davie, G., Ameratunga, S., Wyeth, E., Colhoun, S., Wilson, S., Samaranayaka, A., Lilley, R., Hokowhitu, B., Hansen, P., & Langley, J. (2011). Prospective outcomes of injury study: Recruitment, and participant characteristics, health and disability status. Injury Prevention, 17(6), 415–418.
Accident Compensation Corporation. (2021). Tū Tira Stronger Together: Pūrongo-a-tau Annual Report 2021. Accident Compensation Corporation.
EuroQol Group. EQ-5D-5L | About. Retrieved September 20, 2021, from https://euroqol.org/eq-5d-instruments/eq-5d-5l-about/
Cram, F. (2014). Improving Māori access to health care: Research report. Katoa Ltd.
Jansen, P., Bacal, K., & Crengle, S. (2008). He Ritenga Whakaaro: Māori experiences of health services. Mauri Ora Associates.
Mauri Ora Associates. (2010). Māori experience of ACC Mauri Ora Associates final report for Department of labour. Mauri Ora Associates.
Maclennan, B., Wyeth, E., Hokowhitu, B., Wilson, S., & Derrett, S. (2013). Injury severity and 3-Month outcomes among Māori: Results from a New Zealand prospective cohort study. New Zealand Medical Journal, 126(1379), 39–49.
Wyeth, E. H., Maclennan, B., Lambert, M., Davie, G., Lilley, R., & Derrett, S. (2018). Predictors of work participation for Maori 3 months after injury. Archives of Environmental & Occupational Health, 73(2), 79–89.
McCarty, G. K., Wyeth, E.H., Harcombe, H., Davie, G. and Derrett, S. (2018). Māori Injury and Disability Information Sheet. Ngāi Tahu Māori Health Research Unit, Dunedin, NZ. https://www.otago.ac.nz/maori-health-research/publications/otago688002.html#other
Fahrmeir, L., Kneib, T., Lang, S., & Marx, B. D. (2021). Regression: Models, methods and applications (2nd ed.). Springer.
Stevenson, M., Segui-Gomez, M., Lescohier, I., Di Scala, C., & McDonald-Smith, G. (2001). An overview of the injury severity score and the new injury severity score. Injury Prevention, 7(1), 10–13.
Zou, G. (2004). A modified poisson regression approach to prospective studies with binary data. American Journal of Epidemiology, 159(7), 702–706.
StataCorp LP. (1985-2013). 13.1 ed. College Station, TX, USA.
Statistics New Zealand - Tatauranga Aotearoa. (2006). Census of Population and Dwellings. 2006. Retrieved March 22, 2022 from https://statsnz.contentdm.oclc.org/digital/collection/p20045coll2/id/1219.
Statistics New Zealand. (2001). New Zealand standard classification of occupations. Statistics New Zealand.
Lilley, R., Davie, G., Langley, J., Ameratunga, S., & Derrett, S. (2013). Do outcomes differ between work and non-work-related injury in a universal injury compensation system? Findings from the New Zealand prospective outcomes of injury study. BMC Public Health, 13(1), 995.
Langley, J., Derrett, S., Davie, G., Ameratunga, S., & Wyeth, E. (2011). A cohort study of short-term functional outcomes following injury: the role of pre-injury socio-demographic and health characteristics, injury and injury-related healthcare. Health & Quality of Life Outcomes, 9, 68.
Statistics New Zealand - Tatauranga Aotearoa. (2007). Household Economic Survey 2006-07. Retrieved March 22, 2022 from https://statsnz.contentdm.oclc.org/digital/collection/p20045coll2/search/searchterm/household%20economic%20survey/field/source/mode/exact/conn/and
Derrett, S., Samaranayaka, A., Wilson, S., Langley, J., Ameratunga, S., Cameron, I. D., Lilley, R., Wyeth, E., Davie, G., & Laks, J. (2012). Prevalence and predictors of sub-acute phase disability after injury among hospitalised and non-hospitalised groups: A longitudinal cohort study. PLoS ONE, 7(9), 1–13.
Ministry of Health - Manatū Hauora. (2010). 2006/07 New Zealand health survey: Adult Questionnaire. Retrieved June 25, 2013 from http://www.health.govt.nz/nz-health-statistics/national-collections-and-surveys/surveys/technical-documentation.
American Psychiatric Association Committee of Nomentclature and Statistics. (1980). Diagnostic and statistical manual of mental disorder - (3rd ed.). American Psychiatric Association.
Schwarzer, R., & Jerusalem, M. (1995). Generalized self-efficacy scale. In J. Weinman, S. Wright, & M. Johnston (Eds.), Measures in health psychology: A user’s portfolio casual and control beliefs (pp. 35–37). NFER-NELSON.
Bush, K., Kivlahan, D. R., McDonell, M. B., Fihn, S. D., & Bradley, K. A. (1998). The AUDIT Alcohol Consumption Questions (AUDIT-C): An effective brief screening test for problem drinking. Archives of Internal Medicine, 158(16), 1789–1795.
Sport and Recreation New Zealand. (2004). The New Zealand physical activity questionnaires. SPARC.
Ministry of Health. (2012). National minimum dataset (Hospital Events) data dictionary. Retrieved June 25, 2013 from http://www.health.govt.nz/publication/national-minimum-dataset-hospital-events-data-dictionary.
Sullivan, T., Turner, R. M., Derrett, S., & Hansen, P. (2021). New Zealand population norms for the EQ-5D-5L constructed from the personal value sets of participants in a national survey. Value Health, 24(9), 1308–1318.
Maclennan, B., Wyeth, E., Samaranayaka, A., & Derrett, S. (2022). Predictors of EQ-5D-3L outcomes amongst injured Māori: 1-year post-injury findings from a New Zealand cohort study. Quality of Life Research, 31(6), 1689–1701.
Hajek, A., Brettschneider, C., Mallon, T., Kaduszkiewicz, H., Oey, A., Wiese, B., Weyerer, S., Werle, J., Pentzek, M., Fuchs, A., Conrad, I., Luppa, M., Weeg, D., Mösch, E., Kleineidam, L., Wagner, M., Scherer, M., Maier, W., Riedel-Heller, S. G., & König, H. H. (2022). Social support and health-related quality of life among the oldest old - longitudinal evidence from the multicenter prospective AgeCoDe-AgeQualiDe study. Quality of Life Research, 31(6), 1667–1676.
Cacioppo, J. T., & Cacioppo, S. (2014). Social relationships and health: The toxic effects of perceived social isolation. Social and Personality Psychology Compass, 8(2), 58–72.
Teo, A. R., Choi, H., Andrea, S. B., Valenstein, M., Newsom, J. T., Dobscha, S. K., & Zivin, K. (2015). Does mode of contact with different types of social relationships predict depression in older adults? Evidence from a nationally representative survey. Journal of the American Geriatrics Society, 63(10), 2014–2022.
Macdonald, B., Luo, M., & Hülür, G. (2021). Daily social interactions and well-being in older adults: The role of interaction modality. Journal of Social and Personal Relationships, 38(12), 3566–3589.
Langley, J., Davie, G., Wilson, S., Lilley, R., Ameratunga, S., Wyeth, E., & Derrett, S. (2013). Difficulties in functioning 1 year after injury: The role of preinjury sociodemographic and health characteristics, health care and injury-related factors. Archives of Physical Medicine and Rehabilitation, 94(7), 1277–1286.
Allen, S. A., Dal Grande, E., Abernethy, A. P., & Currow, D. C. (2016). Two colliding epidemics – obesity is independently associated with chronic pain interfering with activities of daily living in adults 18 years and over; a cross-sectional, population-based study. BMC Public Health, 16(1), 1034.
Okifuji, A., & Hare, B. D. (2015). The association between chronic pain and obesity. Journal of Pain Research, 8, 399–408.
Heuch, I., Heuch, I., Hagen, K., & Zwart, J. A. (2013). Body mass index as a risk factor for developing chronic low back pain: a follow-up in the Nord-Trøndelag health study. Spine (Phila Pa 1976), 38(2), 133–139.
Mork, P. J., Holtermann, A., & Nilsen, T. I. (2013). Physical exercise, body mass index and risk of chronic arm pain: Longitudinal data on an adult population in Norway. European Journal of Pain, 17(8), 1252–1258.
Haukka, E., Ojajärvi, A., Takala, E. P., Viikari-Juntura, E., & Leino-Arjas, P. (2012). Physical workload, leisure-time physical activity, obesity and smoking as predictors of multisite musculoskeletal pain. A 2-year prospective study of kitchen workers. Occupational and Environmental Medicine, 69(7), 485–492.
Norton, L., Harrison, J. E., Pointer, S., & Lathlean, T. (2011). Obesity and injury in Australia: a review of the literature. Australian Institute of Health and Welfare.
Finkelstein, E. A., Chen, H., Prabhu, M., Trogdon, J. G., & Corso, P. S. (2007). The relationship between obesity and injuries among U.S. adults. Am J Health Promo, 21(5), 460–468.
Stroud, T., Bagnall, N. M., & Pucher, P. H. (2018). Effect of obesity on patterns and mechanisms of injury: Systematic review and meta analysis. International Journal of Surgery, 56, 148–154.
Barry, R., Modarresi, M., Aguilar, R., Sanabria, J., Wolbert, T., Denning, D., Thompson, E., & Sanabria, J. (2019). The impact of BMI on adult blunt trauma outcomes. The American Surgeon, 85(12), 1354–1362.
Bialowolski, P., Weziak-Bialowolska, D., Lee, M. T., Chen, Y., VanderWeele, T. J., & McNeely, E. (2021). The role of financial conditions for physical and mental health. Evidence from a longitudinal survey and insurance claims data. Social Science & Medicine, 281, 114041.
Binder, N., Blümle, A., Balmford, J., Motschall, E., Oeller, P., & Schumacher, M. (2019). Cohort studies were found to be frequently biased by missing disease information due to death. Journal of Clinical Epidemiology, 105, 68–79.
Brasel, K., deRoon-Cassini, T., & Bradley, C. (2010). Injury severity and quality of life: Whose perspective is important? Journal of Trauma, 68(2), 263–268.
Chiu, K. B., deRoon-Cassini, T. A., & Brasel, K. J. (2011). Factors identifying risk for psychological distress in the civilian trauma population. Academic Emergency Medicine, 18(11), 1156–1160.
Mason, S., Wardrope, J., Turpin, G., & Rowlands, A. (2002). The psychological burden of injury: An 18 month prospective cohort study. Emergency Medicine Journal, 19(5), 400.
Iezzoni, L. I., McCarthy, E. P., Davis, R. B., & Siebens, H. (2001). Mobility difficulties are not only a problem of old age. Journal of General Internal Medicine, 16(4), 235–243.
Nielsen, C. S., Stubhaug, A., Price, D. D., Vassend, O., Czajkowski, N., & Harris, J. R. (2008). Individual differences in pain sensitivity: Genetic and environmental contributions. Pain, 136(1), 21.
Brown, W. J., Bauman, A. E., Bull, F. C., & Burton, N. W. (2012). Development of evidence-based physical activity recommendations for adults (18–64 years). Department of Health and Aged Care.
Reiner, M., Niermann, C., Jekauc, D., & Woll, A. (2013). Long-term health benefits of physical activity – a systematic review of longitudinal studies. BMC Public Health, 13(1), 813.
Babor TF, Higgins-Biddle JC, Saunders JB, Monteiro MG. (2001). AUDIT: The Alcohol Use Disorders Identification Test - guidelines for use in primary care Department of Mental Health and Substance Dependence, World Health Organization Geneva
Saunders J. (2022). AUDIT: Alcohol Use Disorders Identification Test - AUDIT Derivatives. Retrieved July 27, 2022 from https://auditscreen.org/publications/audit-derivatives
Chikritzhs, T., Stockwell, T., Naimi, T., Andreasson, S., Dangardt, F., & Liang, W. (2015). Has the leaning tower of presumed health benefits from “moderate” alcohol use finally collapsed? Addiction, 110(5), 726–727.
Stockwell, T., Zhao, J., Panwar, S., Roemer, A., Naimi, T., & Chikritzhs, T. (2016). Do, “Moderate” drinkers have reduced mortality risk? A systematic review and meta-analysis of alcohol consumption and all-cause mortality. Journal of Studies on Alcohol and Drugs, 77(2), 185–198.
Kerr, W. C., Fillmore, K. M., & Bostrom, A. (2002). Stability of alcohol consumption over time: evidence from three longitudinal surveys from the United States. Journal of Studies on Alcohol, 63(3), 325–333.
Smith, G. (2018). Step away from stepwise. Journal of Big Data, 5(1), 1–12.
Langley, J. D., Lilley, R., Wilson, S., Derrett, S., Samaranayaka, A., Davie, G., Ameratunga, S. N., Wyeth, E. H., Hansen, P., & Hokowhitu, B. (2013). Factors associated with non-participation in one or two follow-up phases in a cohort study of injured adults. Injury Prevention, 16, 2013.
Wilson, R., Derrett, S., Hansen, P., & Langley, J. (2012). Retrospective evaluation versus population norms for the measurement of baseline health status. Health & Quality of Life Outcomes, 10(1), 68–73.
Palmer, S. C., Gray, H., Huria, T., Lacey, C., Beckert, L., & Pitama, S. G. (2019). Reported Māori consumer experiences of health systems and programs in qualitative research: a systematic review with meta-synthesis. International Journal for Equity in Health, 18(1), 163.
Acknowledgements
The authors are grateful to the study participants for sharing their information with us.
Funding
Open Access funding enabled and organized by CAUL and its Member Institutions. The study was funded by the Health Research Council of New Zealand (2007–2013: Project Grant 10/052; 2019-2022: Project Grant 19/325) and co-funded by the Accident Compensation Corporation (2007–2010). The funders took no part in the design of the study nor the collection and analysis of the data.
Author information
Authors and Affiliations
Contributions
BM led the preparation of the paper and drafted the manuscript alongside EW and SD. BM undertook the analyses and interpreted the findings with EW and SD. SD leads the Prospective Outcomes of Injury Study and EW the POIS-10 Māori Study. All authors were involved in finalising the manuscript, and have read and approved the final version.
Corresponding author
Ethics declarations
Conflict of interest
SD is a member of the EuroQol Group (and Executive Committee) which is responsible for the development of the EQ-5D-3L and EQ-5D-5L measures reported in this paper. BM and EW have no conflicts of interest to declare that are relevant to the content of this article.
Ethical approval
Ethical approval for the study was granted by the NZ Health and Disability Multi-region Ethics Committee (MEC/07/07/093/AM07).
Consent to participate
Informed consent was obtained from all individual participants included in the study.
Consent for publication
Study participants consented to their data being published in summary form when providing informed consent to participate in the study.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Maclennan, B., Derrett, S. & Wyeth, E. Health-related quality of life 12 years after injury: prevalence and predictors of outcomes in a cohort of injured Māori. Qual Life Res 32, 2653–2665 (2023). https://doi.org/10.1007/s11136-023-03419-9
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11136-023-03419-9