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. 2021 May 24;11:10797. doi: 10.1038/s41598-021-90142-5

The limit of tolerable micromotion for implant osseointegration: a systematic review

Nupur Kohli 1, Jennifer C Stoddart 1, Richard J van Arkel 1,
PMCID: PMC8144379  PMID: 34031476

Abstract

Much research effort is being invested into the development of porous biomaterials that enhance implant osseointegration. Large micromotions at the bone-implant interface impair this osseointegration process, resulting in fibrous capsule formation and implant loosening. This systematic review compiled all the in vivo evidence available to establish if there is a universal limit of tolerable micromotion for implant osseointegration. The protocol was registered with the International Prospective Register for Systematic Reviews (ID: CRD42020196686). Pubmed, Scopus and Web of Knowledge databases were searched for studies containing terms relating to micromotion and osseointegration. The mean value of micromotion for implants that osseointegrated was 32% of the mean value for those that did not (112 ± 176 µm versus 349 ± 231 µm, p < 0.001). However, there was a large overlap in the data ranges with no universal limit apparent. Rather, many factors were found to combine to affect the overall outcome including loading time, the type of implant and the material being used. The tables provided in this review summarise these factors and will aid investigators in identifying the most relevant micromotion values for their biomaterial and implant development research.

Subject terms: Biological models, Bone, Preclinical research, Biomedical engineering, Implants

Introduction

Metallic protheses implanted directly into bone have revolutionised the treatment of dental, orthopaedic and spinal disease, pain and trauma, with millions of procedures performed annually worldwide1. This has resulted in a continued drive from research centres of excellence and industry to develop new technology that improves outcomes, reduces revision rates, and enables treatment for more patients’ groups, such as those that are younger and more active.

In silico and in vitro modelling are at the heart of the pre-clinical development process for new implant technologies. In the field of implant fixation, a common parameter investigated is the amount of oscillatory micromotion at the bone-implant interface24. Micromotion is the temporary localised relative movement that occurs between an implant surface and adjacent bone when functional loading is applied5,6; with any permanent displacement known as subsidence/migration. These sub-millimetre (hence micro) motions are too small to be seen by the naked eye. Micromotion is the result of primary implant instability and differing bone/implant material moduli, and consequently depends on the implant material, bone density, implant/bone geometry, surgical technique, and the level of interference fit, as well as the magnitude and direction of the applied loading49.

Micromotion is investigated as in vivo data suggest that too much of it leads to failed implant osseointegration: a fibrous capsule forms around the implant rather than a direct structural and functional connection between the host bone and implant10,11. Failed osseointegration leads to aseptic implant loosening, implant failure and the need for expensive revision surgery, both financially and in terms of quality of life12. Thus, much research time and resource has been invested to ensure new implant designs and surgical techniques result in acceptable/improved micromotion at the bone-implant interface1322. There even exists an ASTM standard (F2537–06) to ensure micromotion is measured accurately and repeatably.

Micromotion data are often compared to a limit, below which the implant is considered to pass/be suitable for clinical use, and above which it is considered to be at risk of failed osseointegration. Early in vivo research suggested an upper limit of 150 µm of micromotion and over time this value has become an oft-cited gold standard3,2328. However, the evidence in the 1990s for the 150 µm limit was inconclusive and much time has subsequently elapsed meaning that there is likely much more data available with which to draw conclusions about the relationship between micromotion and osseointegration2931.

This systematic review aimed to compile all the quantitative in vivo evidence relating micromotion to osseointegration to answer the following research questions: (1) Is there value of micromotion that can be universally used as a limit for in vitro or in silico modelling? (2) To what extent is micromotion correlated with bone-implant contact? (3) Which factors influence the relationship between micromotion and osseointegration?

Results

Study selection and characteristics

284 unique records were identified from the databases (Fig. 1). After initial screening, 218 articles were excluded leaving 66 studies for full article screening. An additional 6 studies that passed all inclusion criteria were identified from these 66 studies. After full-text screening, 25 studies were found to be eligible for the quantitative analysis (Table 1).

Figure 1.

Figure 1

Flowchart of the study selection process.

Table 1.

Osseointegrated (OI) and non-osseointegrated (Non-OI) values of micromotion (µm) from the studies selected

Author Year Country Micromotion OI (µm) Micromotion Non-OI (µm) Applied or measured Animal or Human
Aspenberg32 1992 Sweden N/A 500 Applied Animal
Bragdon33 1996 USA 20 40,150
Duyck34 2006 Belgium 60 30,90
Goodman a35 1995 USA N/A 500,500
Goodman b31 1993 Sweden 750 750
Goodman c36 1994 Sweden 500*0 500
Goodman d37 1993 Sweden 500 500
Jakobsen a 38 2015 Denmark N/A 500
Jakobsen b39 2017 Denmark N/A 500,500
Jasty40 1997 USA 20 40,150
Kawahara29 2003 Japan 30 580,630
Overgaard41 1996 Denmark 150*0 150 *12
Soballe a42 1992 Denmark N/A 500,500
Soballe b43 1992 Denmark 150 150
Vandamme a30 2007 Belgium 30,50 30
Vandamme b44 2007 Belgium 30,90 N/A
Vandamme c45 2008 Belgium 30,30 N/A
Vandamme d46 2007 Belgium 30,30 N/A
Manley25 1995 USA 33 ± 23.7, 17 ± 4.2 N/A Measured
Pilliar47 1986 Canada 28 150
Trisi a48 2017 Italy 77.9 ± 17.29, 75.3 ± 19 N/A
Trisi b8 2015 Italy 64 ± 27 177 ± 87
15 ± 5 ,22 ± 6 N/A
Trisi c49 2016 Italy 94.88 ± 10.94, 60.45 ± 5.29 N/A
Trisi d50 2016 Italy 161.26 ± 134.39 619.5 ± 328.26
Engh51 1992 USA  < 40 150 Measured Human

For applied values, the value was set as a controlled experimental parameter, for measured values means and standard deviation are reported where possible. *0 represents experiments with immobilized implants after a period of loading. *12 represents experiments that applied an additional implant displacement for 12 weeks.

Micromotion and osseointegration

One human and twenty-four animal studies were identified (Table 1). For the human post-mortem study, the micromotion for osseointegrated hip stems was less than 40 µm which compared to 150 µm for a stem with failed bone ingrowth. For the animal studies, the mean value of micromotion for implants that osseointegrated was 32% of the mean value for those that did not (112 ± 176 µm osseointegrated versus 349 ± 231 µm non-osseointegrated, Mann Whitney test p < 0.001, Fig. 2). However, the osseointegration outcome also depended on other experimental/implant conditions with no distinct osseointegration limit detected. Rather, the range for successful/failed osseointegration overlapped: 15 to 750 µm for osseointegrated samples versus 30 to 750 µm for non-osseointegrated samples (Table 1 and Fig. 2).

Figure 2.

Figure 2

(A) Scatterplot of the animal data showing the micromotion value for osseointegrated (green, circle, n = 28) and non-osseointegrated (hollow circles, n = 23) samples. (B) Violin plot of the same data. Whilst micromotion was lower for the osseointegrated samples (Mann Whitney test p < 0.001), there was also considerable overlap between the groups.

The effects of research method: applied vs measured micromotion

When micromotion was applied, lower micromotion resulted in more consistent osseointegration (Fig. 3A, Mann Whitney p value = 0.001). Similarly, when micromotion was measured at the end of the study duration, implants that osseointegrated had lower micromotion than implants that did not (Fig. 3B, Mann Whitney p value = 0.01). Comparing values of micromotion between the methods (measured vs applied), no differences were observed for the osseointegrated group, and similarly there was no difference between the methods for the non-osseointegrated group. (Fig. 3).

Figure 3.

Figure 3

(A) Applied values of micromotion in osseointegrated (OI, n = 17) and non-osseointegrated (Non-OI, n = 20) groups for the animal studies. Mann Whitney p value = 0.001 **. (B) Measured values of micromotion in OI (n = 11) and non-OI (n = 3) for the animal studies. Mann Whitney p value = 0.003 **.

Micromotion and bone-implant-contact

Out of the 24 animal studies, 13 studies examined osseointegration as the percentage of BIC, 2 studies reported on bone ingrowth and 1 study reported on both BIC and bone ingrowth. For implants that were defined as osseointegrated, a positive correlation was observed between micromotion and % BIC (Spearman’s ρ = 0.41, p value = 0.02). Micromotion and BIC were not correlated for the non-osseointegrated group (p value = 0.39), nor the full dataset (p value = 0.07).

Observation time and Bone-implant-contact

There was a positive correlation between observation time and percentage BIC, with longer study duration time resulting in better percentage BIC (Spearman’s ρ = 0.40, p value = 0.01).

Discussion

The most important finding of this systematic review was that the available data refutes the idea of a universal limit of tolerable micromotion for implant osseointegration. Whilst on average, the micromotion associated with osseointegration was 32% of the micromotion associated with failed fixation, many exceptions to the rule were identified (Fig. 2). In some studies, micromotion at the bone-implant interface as high as 750 µm osseointegrated, whilst in other micromotion as low as 30 µm did not osseointegrate. Thus, implant and external factors must be considered when estimating the level of micromotion that could lead to successful osseointegration for a new biomaterial/implant. The following implant factors were associated with higher levels of micromotion and successful osseointegration: hydroxyapatite coating43, larger threads in lower density bone8, and square pore cross-sectional shape37. The following environmental factors were associated with higher levels of micromotion and successful osseointegration: infrequent loading31, a rest period following initial loading41 and longer study duration (9 weeks or more)30,44 (Table 2).

Table 2.

Detailed study characteristics of the selected studies.

Author Year No. of animals or patients Species No. of samples (per group) No. of study groups Implant material Implant coating or implant type Bone Time (weeks) Loading conditions Loading cycles and time Micromotion (µm) Bone ingrowth Bone-implant-contact
Osseo-integrated Non-osseo-integrated
Aspenberg 1992 6 rabbits 13 2 titanium none Tibia 3 Unloaded N/A Unloaded Not measured
15 3 500 µm Micromotion 20 cycles/day 500
Bragdon 1996 20 Dogs 5 4 Titanium None Femur 6 UNLOADED N/A Unloaded Not measured
6 20 µm Micromotion 8 h/day 20
6 40 µm micromotion 8 h/day 40
6 150 µm micromotion 8 h/day 150
Duyck 2006 10 Rabbits 10 4 Titanium None Tibia 6 Unloaded Unloaded 20–25%
6 30 µm micromotion 800 cycles/day; twice/week 30 5–10%
6 60 µm micromotion 800 cycles/day; twice/week 60 15–20%
6 90 µm micromotion 800 cycles/day; twice/week 90 5–10%
Goodman a 1995 9 Rabbits 9 4 Titanium Micromotion alone Femur 3 500 µm micromotion 40 cycles/day 500 25 ± 6
Polyethylene particles only 3 Unloaded N/A Unloaded 23 ± 9
No polyethylene 3 Unloaded N/A Unloaded 33 ± 6
polyethylene + micromotion 3 500 µm micromotion 40 cycles/day 500 23 ± 9
Goodman b 1993 7 Rabbits 7 3 Titanium None 3 Unloaded Unloaded 31 ± 2%
10 Tibia 3 750 µm micromotion 20 cycles/day 750 46 ± 5%
7 3 750 µm micromotion 20 cycles twice/day 750 19 ± 7%
Goodman c 1994 5 Rabbits 5 3 Titanium None Tibia 6 500 µm micromotion (3 weeks), then unloaded (3 weeks) 40 cycles/day then unloaded 500 37 ± 7
3 500 µm micromotion 500 20 ± 2
3 Unloaded N/A unloaded 37 ± 6
Goodman d 1993 10 Rabbits 6 2 Titanium Square chamber Tibia 3 500 µm micromotion 20 cycles/day 500 not measured
5 Round chamber 3 500 µm micromotion 20 cycles/day 500 not measured
Jakobsen a 2015 10 Sheep 10 2 PMMA Femur 12 500 µm micromotion Every gait cycle Unloaded 500
Jakobsen b 2017 10 Sheep 10 2 PMMA Control Femur 12 500 µm micromotion Every gait cycle 500
Zoledronate 12 500 µm micromotion Every gait cycle 500
Jasty 1997 20 Dogs 5 4 Titanium None Femur 6 Unloaded N/A Unloaded 9.3 ± 2.3
6 20 µm micromotion 8 h/day 20 9.0 ± 3.1
6 40 µm micromotion 8 h/day 40 11.8 ± 3.9
6 150 µm micromotion 8 h/day 150 10.4 ± 3.0
Kawahara 2003 Beagles Titanium None Mandi-ble 6 8 N 10 s 30 580, 630 not measured
Overgaard 1996 14 Dogs 7 2 Titanium Hydroxyapatite coated Femur 16 150 µm micromotion (4 weeks), then unloaded (12 weeks) Everyday 150 28.5 ± 8.8 54.6 ± 10.0
16 150 µm micromotion Everyday 150 24.1 ± 16.1 37.7 ± 10.1
Soballe 1992 14 Dogs 8 4 Titanium Hydroxyapatite coated Femur 4 500 µm micromotion every gait cycle 500 0–10%
Hydroxyapatite coated 4 Unloaded N/A unloaded 45%
Titanium coated 4 500 µm micromotion every gait cycle 500 0–10%
Titanium coated 4 Unloaded N/A Unloaded 0–10%
Soballe 1992 14 Dogs 7 4 Titanium Hydroxyapatite coated Femur 4 150 µm micromotion Every gait cycle 150 7 ± 2
Hydroxyapatite coated 4 unloaded N/A unloaded 65 ± 2
Titanium coated 4 150 µm micromotion Every gait cycle 150 0
Vandamme a 2007 14 Rabbits 10 3 Titanium None Tibia 12 Unloaded N/A unloaded 0–20%
10 6 30 µm micromotion 400 cycles/day ; twice/week 30 0–20%
11 12 30 µm micromotion (6 weeks), then 50 µm micromotion (6 weeks) 400 cycles/day; twice/week, then 800 cycles/day; twice/week 30, 50 60–80%
Vandamme b 2007 10 rabbits 10 3 Titanium none Tibia 9 Unloaded unloaded 42.22
9 30 µm micromotion 400 cycles/day; thrice/week 30 71.43
9 90 µm micromotion 400 cycles/day; thrice/week 90 74.36
Vandamme c 2008 20 Rabbits 10 2 Titanium Turned Tibia 9 Unloaded N/A unloaded 6.98
Turned 9 30 µm micromotion 400 cycles/day; thrice/week 30 53.33
Roughened 9 Unloaded N/A Unloaded 42.22
Roughened 9 30 µm micromotion 400 cycles/day; thrice/week 30 71.43
Vandamme d 2007 10 Rabbits 10 3 Titanium screw Tibia 9 Unloaded N/A unloaded 0–3%
screw 9 30 µm micromotion 400 cycles/day; thrice/week 30 9–20%
cylindrical 9 30 µm micromotion 400 cycles/day; thrice/week 30 0–8%
titanium 4 Unloaded N/A Unloaded 13 ± 3
Manley 1995 12 Dogs 6 2 Titanium Collared Femur 16  ± 50 N 16 s at 0.5 Hz 33 ± 23.7 52 ± 11.4
Collarless 16  ± 50 N 16 s at 0.5 Hz 17 ± 4.2 42 ± 8.5
Pilliar 1986 Dogs 5 3 Cobalt Chrome Femur 52 28 150
Trisi a 2017 2 sheep 10 2 Titanium SLA Iliac crest 8 25 N/mm End point analysis 77.9 ± 17.29 49.49 ± 7.70
FEL 8 25 N/mm End point analysis 75.3 ± 19 65.33 ± 6.35
Trisi b 2015 4 Sheep 20 2 Titanium Large threaded Iliac crest 8 25 N/mm End point analysis 64 ± 27 50.58 ± 8.65
small threaded 8 25 N/mm End point analysis 177 ± 87 40.98 ± 14.03
Large threaded Mandi-ble 8 25 N/mm End point analysis 15 ± 5 36.1 ± 18.3
small threaded 8 25 N/mm End point analysis 22 ± 6 34.06 ± 18.18
Trisi c 2016 2 Sheep 10 2 Titanium Coventional drill Iliac crest 8 25 N/mm End point analysis 94.88 ± 10.94 46.19 ± 3.98
Osseo-densification 8 25 N/mm End point analysis 60.45 ± 5.29 49.58 ± 3.19
Trisi d 2016 2 Sheep 24 2 Titanium Healthy Iliac crest 8 25 N/cm End point analysis 161.26 ± 134.39 44.75 ± 9.77
Failed 8 25 N/cm End point analysis 619.5 ± 328.26 22.6 ± 9.54
Engh 1992 14 (6 female) Human, mean age 71 14 1 Cobalt Chrome Coated hip stem Femur 52–403 Gait & stair climbing N/A  < 40 150

The gold standard micromotion limit is often considered 150 µm. However, Overgaard et al., and Soballe et al., showed that this level of micromotion can be tolerated if a period of rest is allowed after initial loading and if the implant was coated with hydroxyapatite41,43. The accelerated resorption of HA coating under excessive micromotion could have led to a better bony ingrowth as studies have previously shown that HA coating on titanium implants improve BIC through its direct interaction with osteoblast, osteoclasts and pro-inflammatory markers52,53. Further, previous studies have also shown that a period of rest or otherwise referred to as recovery phase may be beneficial for BIC. The recovery phase or time off helps to counteract the waning effects of long-term mechanical loading, and improve the responsiveness of osteoblasts and osteocytes to restart bone formation54,55. Goodman et al., showed that oscillatory motions up to 750 µm once a day would allow successful osseointegration, while the same motions twice a day would not31, emphasizing the effect of loading duration. Similarly, Goodman also demonstrated how implant factors can influence the tolerable micromotion: by changing the pore-cross sectional shape of the outer bone chamber from round to square in the traditional bone chamber designs, bony ingrowth would be facilitated even with micromotions as high as 500 µm.

Whilst the data reviewed revealed that the mean value of micromotion for successful osseointegration was 112 µm, some studies showed that micromotion as low as 30 µm can lead to failed implant fixation30,40. The authors attributed this to the duration of loading, hypothesizing that the process of bone formation had not been reached within 6 weeks. Subsequent experiments measured osseointegration at 9 weeks or more and demonstrated successful osseointegration with the longer study duration30,44. The data from this systematic review further supports this finding, demonstrating a positive correlation between osseointegration (measured by percentage BIC) and study duration (Fig. 4). Biologically, osseointegration starts with woven bone formation, followed a period of remodelling to lamellar bone in response to mechanical loading. This transition from woven bone to lamellar bone formation takes starts around 6–8 weeks and can take a period of months to complete56,57. Therefore, in vivo experimental studies exploring osseointegration of implants should allow a time period of over 6 weeks to see the full healing response. The effects of study duration have also been reflected by recent computational research which highlighted the differing mechanisms between bone healing and remodelling, and hence the importance of the measurement time point2.

Figure 5.

Figure 5

Scatter plot demonstrating the correlation between observation time and percentage BIC for the animal studies. Spearman’s ρ = 0.40, p value = 0.01.

Another explanation for the contradictory in vivo data is that micromotion is a simplified, clinically convenient measure, which overlooks the fundamental mechanobiological mechanisms that drive implant osseointegration. In vivo data coupled with finite element analyses suggest that it is the interfacial stress–strain state resulting from implant micromotion that stimulates osseointegration58,59. Different loading conditions (axial, shear, torsional, etc.), combined with different localised implant/bone geometry lead to different stress–strain states, with too much strain leading to fibrous tissue formation5861. Indeed, by considering the interfacial stress–strain state, it is possible to relate implant bony ingrowth theory2,58,59 to fracture healing theory6265, which intuitively one would expect given the involvement of the same cell types66. Conversely, when the implant/environmental conditions that affect the interfacial stress–strain state are ignored, counter-intuitive trends can be observed. For example, when neglecting these factors, it was found that increased micromotion was positively correlated with increased percentage BIC (Fig. 5). However, within study data demonstrate that micromotion and percentage BIC are negatively correlated50. This further emphasises the needs to consider implant and environmental factors and their link to the interfacial stress–strain state when interpreting how micromotion affects osseointegration. It should also be noted that there is no standard interpretation of BIC and so caution should also be applied when interpreting BIC between studies. Some studies report BIC as the fraction of mineralized bone in direct contact with the implant surface44, whilst other describe it as the length of the implant surface in contact with (both mineralised and non-mineralised) bone relative to the total implant length34.

Figure 4.

Figure 4

Scatter plot graph of the correlation between micromotion values and percentage BIC for the animal studies. For the osseointegrated data (green filled circles) a positive correlation was found (Spearman’s ρ = 0.41, p value = 0.02). No correlation was observed for the non-osseointegrated data (empty circles), nor the full dataset (all circles).

Historically, the causal effect of implant micromotion on osseointegration was investigated by applying known displacement and subsequently measuring osseointegration. However, more recently, research method has shifted to applying known loads and quantifying micromotion at the end of the experiment4,8. Both measurement techniques were able to identify differences in micromotion between implants that osseointegrated and those that did not. Interestingly, when comparing the results between the two different methods, no differences were found.

The majority of studies identified applied micromotion as a controlled experimental condition, meaning that mean and standard deviation micromotion data were not available prohibiting application of the established meta-analysis approaches recommended by Borenstein et al67. For the same reason, it was not possible to perform a cumulative meta-analysis to quantify the risk of bias between studies. Rather, to provide some quantitative analysis we applied Mann Whitney tests to the data extracted from each study. Further we isolated the effects of studies that applied micromotion, and those that measured it, and found that this did not affect the principal finding our systematic review (Fig. 3).

In conclusion, this systematic review has demonstrated that the idea of a universal limit of tolerable micromotion for implant osseointegration is misleading. Rather, implant and environmental factors, and their link to interfacial stress–strain states, must be considered to identify the most appropriate limit for the biomaterial/patient group under consideration. The tables provided in this systematic review summarise the implant and environmental conditions for all published quantitative in vivo micromotion research and will enable investigators to compare their data to the most appropriate values.

Materials and methods

Protocol and registration

Prior to the investigation, the protocol was registered with the International prospective register for systematic reviews PROSPERO (ID: CRD42020196686), following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement and checklist68.

Eligibility criteria

Studies which fulfilled the following criteria were included: (1) in vivo animal research or post-mortem human data where the implant was inserted pre-mortem. (2) testing of osseointegration when micromotion was either applied or measured with micromotion values reported in the form of displacement (3) the study was an original research article; and (4) the studies were published in English.

Articles were excluded if: (1) micromotion was measured indirectly and/or reported as implant stability quotient (ISQ) or resonance frequency analysis (RFA); (2) Study duration less than 3 weeks; (3) Finite element analysis (FEA) or computational studies; (4) cemented implants; (5) cadaveric bone in vitro experiments where prostheses were inserted post-mortem; and (6) synthetic bone in vitro experiments.

Information sources and search strategy

An electronic search was performed for articles published up to 16th November 2020, in the following databases: PubMed, Scopus and Web of Science. The search strategy identified papers which included the following terms: (micromotion OR "micro-motion" OR "micro motion") AND ("osseointegration" OR "osteointegration").

Study selection

Two independent reviewers (N.K., J.S.) assessed the titles and abstracts of all the studies and discarded studies that met any of the exclusion criteria. The full text of all remaining studies was then assessed against the inclusion and exclusion criteria. Any disagreement regarding eligibility of articles were resolved by a third reviewer (R.v.A.).

Data collection process and data items

Data relating to osseointegrated and non-osseointegrated values of micromotion were extracted. The country, animal species, number of study groups, duration of the experiment, implant material and loading conditions were recorded. The outcome of osseointegration measured as bony ingrowth or percentage bone-implant-contact (BIC) were also recorded.

The micromotion methodology (applied or measured) was also recorded. In the applied group, known values of micromotion in the form of cyclic loading were directly applied as a controlled experimental condition and then osseointegration was assessed. In measured group, micromotion was not a controlled experimental condition, rather micromotion at the bone-implant interface was measured once the implant had osseointegrated/not.

Statistical analysis

Data were analysed and plotted using Graph Pad Prism 8 software and have been reported as mean ± standard deviation (SD). Four analyses were performed:

  1. All micromotion values were grouped into osseointegrated/not, according to the definition used by the original study authors. Data were first tested for normality, and then non-parametric Mann Whitney tests were used to compare differences between groups.

  2. Micromotion values were further discretised according to the study method (applied vs measured micromotion). Then analysis 1) was repeated for both of these subgroups.

  3. Spearman correlation tests were used to examine correlation between percentage BIC and micromotion values for three groups: all data, osseointegrated, non-osseointegrated.

  4. Spearman correlation tests were used to examine the correlation between percentage BIC and study duration.

The significance level was set to α = 0.05.

Acknowledgements

This work was supported by UKRI (EPSRC) EP/S022546/1 (N.K. and R.v.A.) and the Peter Stormonth Darling Charitable Trust (J.S.).

Author contributions

N.K. and R.v.A. designed the study. N.K. and J.S. collected and analysed the data. R.v.A. acted as a third reviewed to resolve issues regarding selection of articles for data synthesis. N.K. prepared all the figures and tables. N.K. and R.v.A. wrote the final manuscript. All authors reviewed the manuscript.

Data availability

Data generated and analysed during this study are included in this published article. Data are available from the corresponding author subject to reasonable request.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Data generated and analysed during this study are included in this published article. Data are available from the corresponding author subject to reasonable request.


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