MICRO-EVIDENCE ON DAY LABOURERS AND THE THICKNESS OF LABOUR MARKETS IN SOUTH AFRICA 1

Waldo Krugell
School of Economics
North-West University

Derick Blaauw
School of Economics
North-West University

MICRO-EVIDENCE ON DAY LABOURERS AND THE THICKNESS OF LABOUR MARKETS IN SOUTH AFRICA 1
AE05E31E6F8055A8BCD47B43E5FE71AAAccepted: April 2014day labourerslabour marketagglomeration JEL: J212431R23
The South African labour market is characterised by sharp segmentation, high unemployment and apparently limited informal sector employment.Recent work has focussed on the importance of the quality of education while others have argued that the rigidity of the labour market constrains employment growth.This paper considers the spatial aspects of the day labour market and argues that the size and proximity of economic activity found in agglomerations ensure a thick labour market that allows for better matching between workers and jobs.The results indicate that the day labourers who were hired by the same employer more often received higher earnings.Once workers have a matric qualification they receive earnings above the average, as do workers who have completed vocational training.Skills, as well as factors associated with a thicker labour market are positively associated with wages.The thicker metropolitan labour market allows workers to become more specialised and receive higher earnings.This has important policy implications and calls for the development of people and places.

Introduction

South Africa's unemployment rate is remarkably high and it is most visible in the form of the day labourers who stand at the side of the road or on street corners every day, waiting for any temporary job (Blaauw, Louw & Schenck, 2006:458).South Africa's informal sector is small compared to other developing countries and the observed unemployment is not voluntary (Kingdon & Knight, 2001).Devey, Skinner and Valodia (2002) found that income levels in the informal economy are very low, and race and gender are important determinants of income.This study extends the analysis by examining the correlates of earnings of day labourers, specifically the socalled thickness of the labour market.

Standard explanations of labour market outcomes have focused on the attributes of individuals, specifically the importance of education, as well as on labour market characteristics and social networks.A few authors have also considered the spatial aspects of the labour market and recently Havemann and Kearney (2010) found that urbanisation is an important predictor of wage differentials in the formal sector.This paper expands this line of work by arguing in favour of the Smith-Marshallian view of agglomeration and the labour market.This approach holds that the size and proximity of economic activity found in cities and large towns ensure a thick labour market that allows for better matching between workers and jobs.Two models characterise this approach.Helsley and Strange (1990) showed that a large city allows for a better average match between heterogeneous workers and employers' job requirements and this enhances efficiency.On the other hand, Duranton (1998) argued that a large market allows workers to become more specialised and, therefore, to be more efficient.In both cases, greater efficiency increases workers' wages and this attracts more workers.

Here the focus is on day labourers, drawing on a country-wide survey.Day labouring can be seen as a subset of the employee side of the informal economy in South Africa (Blaauw, 2010).Kingdon and Knight (2004) refer to subsectors of the informal sector and argue in favour of a broader view of informal employment than the traditional informal business-Abstract based approach (see also Fourie, 2011:18).The contribution of the paper is threefold: i) it uses a unique set of primary data collected in the idiosyncratic South African labour market, ii) it adds agglomeration to the labour market discourse, and iii) the geography goes beyond a rural-urban dummy or provincial-level analysis and includes district council-level population density, a measure of occupation density and interactions with a metropolitan areas dummy.The survey data allows us to estimate a crosssection regression model of the importance of the thickness of the labour market as a correlate of day labour wages, while controlling for individual-specific characteristics.The results show that individuals' education and skills, as well as factors associated with a thicker labour market, are positively associated with wages.This has important policy implications and calls for the development of people and places.

The paper is structured as follows.Section 2 provides an overview of the theory of agglomeration and the labour market.A number of claims are identified and tested in the subsequent empirical analysis.We also review South African contributions that have considered the spatial aspects of the labour market.Section 3 presents a description of the survey and descriptive statistics of the data collected.The regression analysis is described and results are reported in Section 4. Section 5 concludes and makes recommendations.

Literature review

Agglomeration and labour markets

A wide variety of theories may be called upon to explain the location, specifically the agglomeration, of production in space.These range from the fields of urban economics, regional economics, trade and growth theories and development economics.The formal model of geographical economics was put forward by Krugman (1991) and discussed in detail by Brakman, Garretsen and van Marrewijk (2001) and Fujita and Thisse (2002).Preceding the mathematical models, Porter (1998) provided an intuitive explanation of the importance of the clustering of economic activity.A cluster is a critical mass of producers in a particular field, in a particular location -the result of the process of localisation.In clusters, the proximity of producers leads to spillovers that improve factor conditions.This improves the flow of information and the success of innovation.This is also true for related and supporting industries.They provide specialised inputs and information, and facilitate complementarities among firms.Materials, components, machinery and services are supplied more efficiently and at lower cost when producers are concentrated in a particular locality.Location plays a role in firm strategy and rivalry.Rivalry that involves imitation and differentiation improves competition and leads to growth.When firms are clustered together, rivalry is more intense.In the final instance, the demand conditions in a locality may influence the business environment, competition, and growth.Sophisticated and demanding customers at home press firms to improve and differentiate and a cluster may provide such a group of customers.Thus, Porter (1998) saw the enduring competitive advantages in a global economy as localised.Proximity allows for relationships, better information and other advantages in productivity and productivity growth.

These reasons why firms locate close to one another has a corollary in the labour market.Proximity allows for better matching between workers and jobs.In this approach there are two models.Helsley and Strange (1990) showed that a large city allows for a better average match between heterogeneous workers and firms' job requirements and this enhances efficiency.On the other hand, Duranton (1998) argued that a large market allows workers to become more specialised and, therefore, to be more efficient.In both cases, the increased efficiency increases workers' wages.At the same time, workers find it less risky to be in locations with many possible employers.Empirical evidence shows that a doubling of economic density increases productivity by six per cent (Ciccone & Hall, 1996) and a doubling of employment density increases productivity by 4.5 to 5 per cent (Ciccone, 2002).

Spatial aspects of the South African labour market

In the case of South Africa, there are few studies that examine the spatial aspects of the labour market.Kingdon and Knight (2004) found that location matters for black unemployment on a national scale.In a later contribution, Kingdon and Knight (2006) examined wage responsiveness to local unemployment.At an aggregate level the difference between the increase in the labour force and the fall in formal sector employment grew rapidly over the period 1990 to 2000, suggesting that there was a positive relationship between wages and unemployment.However, Kingdon and Knight's (2006) estimation of a wage curve across space indicated a negative relationship.The results showed that male, urban and married workers received significantly higher wages than female, rural, unmarried workers.They found that the distinction between rural and urban areas did not capture labour market segmentation well, but significant province dummies indicated regional variation in pay levels.It was also found that centralised bargaining insulates workers from local labour market conditions.Recently, Magruder (2010) examined the last result more closely by looking for spatial discontinuities in the enforcement of centralised bargaining agreements.He used a database of bargaining council agreements along with September Labour Force Survey data for the period 2000 to 2003 with magisterial districts as the spatial level of observation.The results show large spatial discontinuity effects: having a centralised bargaining agreement in a particular industry in a specific town causes employment to be 8 to 15 per cent lower and wages to be 10 to 21 per cent higher than in the same industry in an uncovered neighbouring town.Wittenberg (2001) examined the spatial dimension of unemployment by examining the role of neighbourhood networks.He used data from the 1995 October Household Survey and a distinction between urban and rural households.He found that some households are more successful at getting their members employed than others and there is a difference in these social effects between urban and rural areas.His spillover variable suggested that rural households have better neighbourhood networks that allow them to access labour market opportunities.A more recent contribution by Hofmeyr (2010) examined the link between social networks and ethnic occupa-tional niches in manufacturing.Employing data from the 2001 census, which allows for analysis at the level of magisterial districts, Hofmeyr (2010) used individuals' language groups and magisterial districts as a proxy for their social networks and found strong evidence of niche employment.The results showed that English and Afrikaans individuals are clustered in advantageous niches where monthly income and skill levels are relatively high.

In a slightly different approach, work by Naudé (2008) examined the possibility of a spatial mismatch in the metropolitan labour market as an explanation of the differences in unemployment rates between the white and black populations.He used data from the 1996 and 2001 censuses and employed various methods measuring the extent of suburbanisation of the population and employment, examining the relationship between residential segregation and unemployment, analysing commuting distances and taking into account differences in earnings and education.The results showed that there exists a spatial mismatch between jobs and jobseekers and that distance from the city centre plays a significant role as a predictor of black unemployment.

The latest contribution that examines spatial aspects of the South African labour market comes from Havemann and Kearney (2010) who argue that where you live matters for employment.They used 2001 census data to construct an urbanisation index at district council level and used it along with a range of individual-specific predictors of employment from the Labour Force Survey of March 2005.The results show a positive relationship between urbanisation and the probability of being employed.For example, someone in Johannesburg is 1.5 times more likely to be employed than a similar individual in a medium-sized town.

Finally, there is only one recent study of day labourers.There are of course many contributions to the study of the informal economy, for example Devey et al. (2002), but there the focus is on a wider range of informal activities that falls outside the scope of this review.For the case of day labourers specifically, Harmse, Blaauw and Schenck (2009) examined inter-regional differences in the labour market and found clear differences.Day labourers were found to earn higher levels of income in cities and larger towns than in rural areas.Every city or town has sites where a labourer can earn more income than at other sites.Also, some sites draw together labourers with higher levels of skills.However, their focus was only on general levels of development and unemployment at the provincial and local municipality level.

In summary it can be said that a literature of the spatial aspects of the labour market in South Africa exists and that it seems that location may influence labour market outcomes.This paper takes their analysis a step further by examining location as one of the correlates of earnings while controlling for a range of individual-specific characteristics of day labourers.The key claims to test are whether large urban areas do allow for a better match between workers and jobs, whether it allows for day labourers to become more specialised and if these factors contribute to higher earnings.The following section describes the survey of day labourers (Harmse et al., 2009) through which the data were obtained.Section 4 presents the empirical analysis and results.

3

The survey of day labourers in South Africa

Survey method

Information from all available sources, for example municipalities, churches and other welfare organisations as well as the Department of Labour, was used to plan a systematic process to estimate the number of day labourers in South Africa.The two years preceding the survey were used to go around the country and physically count the number of day labourers in the various cities and towns and to conduct preliminary interviews.During this process the names of the streets where the day labourers congregated were recorded and the number of day labourers present at each site was counted.There are nearly 1,000 places in South Africa where a minimum of 45,000 mostly black African men stand and wait to be picked up for day labour (Harmse et al., 2009:4;Blaauw, 2010:75).

Figure 1 illustrates the geographical distribution of day labourers in South Africa at the local municipality level at the time of the survey.

Figure 1

The spatial distribution of day labourers in South Africa, 2006/07 Source: Survey data; Harmse et al., 2009 A sample of between 5 and 10 per cent was appropriate to control for possible sampling error (De Vos, Strydom, Fouche & Delport, 2004:200).It was estimated that a total of between 2 500 and 4 000 interviews had to be conducted across South Africa in order to obtain a representative sample of the research population (Harmse et al., 2009;Blaauw, 2010:82).For this purpose, a detailed questionnaire was needed.

The questionnaire that was used in the 2004 Pretoria survey (Blaauw et al., 2006) laid the foundation for the formulation of the questionnaire for conducting countrywide interviews.The questionnaire was designed in a multi-stage process.The draft was furthermore subjected to a trial run before the final adjustments were made.

A dedicated fieldworker, who could speak several of the official languages of South Africa, was hired and she received extensive training.In the bigger metropolitan areas students in the Department of Social Work at UNISA were recruited and thoroughly trained as additional fieldworkers.The fieldwork commenced towards the end of February 2007 and was completed by the beginning of 2008 (Harmse et al., 2009).The sample was checked to ensure that the required proportionality in terms of the regional distribution was maintained (Blaauw, 2010:90).The results of the descriptive analysis and subsequent empirical work are presented in the next sections.

Descriptive statistics

This paper uses the responses to the survey of 3,812 day labourers.Of these, the majority were male (96 per cent) and Black (92 per cent).A quarter of the respondents were found in the Gauteng province, 16 per cent in the Western Cape, 14 per cent in KwaZulu-Natal and 11 per cent in the Eastern Cape province.Figure 2 shows the age distribution of the respondents.Most of the day labourers surveyed were between 20 and 40 years of age.Only 2.5 per cent were younger than 20 years and only 4.8 per cent were older than 50 years.It is clear that most of the day labourers (49 per cent) had some secondary schooling and approximately 15 per cent had completed their secondary schooling.In terms of training or courses completed, 13 per cent indicated that they had completed a bricklaying course, 17 per cent a painter's course and 11 per cent had carpentry training.Approximately 31 per cent indicated that they had other training or courses completed.A cross tabulation of the qualifications and training measures shows a correspondence between higher levels of education and the more high-skilled vocational training.Day labourers who had some secondary schooling had also completed courses in bricklaying (15.8 per cent) and painting (14.3 per cent).Some that completed secondary school also had training as carpen-ters (14.8 per cent), or tilers (13.3 per cent).

Of the total group surveyed, 51 per cent indicated that they had at one time held a fulltime job.They were also asked how frequently the same employer hired them for three days or more.Half indicated that this seldom happened, while almost a quarter said that it happened sometimes and 15 per cent said that it happens often.The questionnaire also asked what kind of jobs they had as a day labourer in the last month.The interviewers marked the kind of jobs that were mentioned on a list of 20 possibilities and an 'other' option.On average, the workers mentioned three kinds of jobs that they had in the last month.Table 1 shows the results.grouped by the skills required.Some workers do the bricklaying, plastering and painting, electricians and their assistants are a group on their own, while others do carpentry and roofing and work as plumbing assistants.On average all these day labourers had been working in such jobs for almost four years.

The survey also asked the labourers how much they earned during a good and a bad week.For the group as a whole, earnings in a good week averaged R386 and R163 in a bad week.Figure 4 shows a scatter of the earnings in a good week and the difference between earnings in a good and a bad week.The observations are sorted from low to high earnings in a good week.It is clear that there is a significant spread of values around the mean of R386 -the standard deviation is R304.When a bad week's earnings are brought into the picture, the spread widens, particularly among those day labourers that earn above average in a good week.

Figure 4

Earnings in a good week and the difference between earnings in a good and a bad week

The variation in earnings from the average is what this paper wants to focus on and there are many interesting differences.Table 2 presents the means of earnings in a good week, split by a number of possible correlates.Examination of the age distribution shows that those day labourers between the ages of 26 and 45 generally receive above average incomes, while younger and older workers receive incomes below the average.Some of the variation in earnings is due to level of education.Table 2 shows that day labourers who have completed secondary school or have a post-school qualification have substantially higher earnings in a good week.All the workers who have completed vocational training or a course of some kind receive earnings above the average.Surprisingly, workers that have never held a full-time job, on average, receive higher incomes than those that have held a full-time job.This may well be an indication that social and psychological aspects also influence these labour market outcomes.A day labourer who was used to more stable employment may be more despondent and therefore not look for employment with the same vigour as his colleague who never had anything better in terms of previous employment.It may be that they do not have the same networks of employment information.This opens the opportunity for in-depth qualitative interviews and focus group discussions with day labourers to verify these hypotheses.

As day labourers, those that are often hired by the same employers for three or more days, earn much higher incomes.The type of work done also helps to explain the variation in earnings.Table 1 showed that bricklayers, electricians, carpenters, painters and those in roofing do substantially better than their assistants.Digging and shovelling, carpenter's assistants, roofing assistants, car washing, plastering, electrician's assistants and plumbers also receive above average incomes in a good week.Where principle component analysis was used to group the different types of jobs done by different day labourers, it is possible to use cluster analysis to regroup those labourers by earnings and types of jobs.

Simple two-step cluster analysis reveals two distinct clusters.Cluster 1 consists of the more unskilled jobs such as loading and unloading, construction demolition and clean-up, domestic work, car wash and gardening, as well as farming activities.It also includes work as an assistant, such as bricklaying assistant, painting assistant, and plumbing assistant.Cluster 2 consists of the hard physical labour of digging and shovelling and the more skilled construction jobs such as bricklaying, roofing, roofing assistant, carpentry, carpentry assistant, painting, electrician, electrician assistant and plastering.The difference in earnings is as expected, with the workers in more unskilled jobs receiving below average earnings and those in more skilled jobs receiving above average income in a good week.In section 2 it was argued that large urban areas do allow for a better match between workers and jobs, and this allows day labourers to become more specialised.A cross tabulation of the frequency of employment and metropolitan areas indicator shows that in metro areas 22 per cent of day labourers are often hired by the same employer for more than three days, compared to 13 per cent in other areas.When one considers the variety of jobs done by day labourers (the number of jobs that they reported doing as a proportion of the total of twenty job types), those in metro areas are more specialised.They have a variety mean of 0.117 with a standard deviation of 0.082, whereas those workers elsewhere have a variety mean of 0.178 and a standard deviation of 0.113.Table 2 shows that location may also matter as a possible explanation of the variation in earnings.Day labourers in the Western Cape, Gauteng and KwaZulu-Natal receive above average earnings in a good week, whereas those in the Limpopo Province, the Free State and Northern Cape do particularly poorly.The metropolitan areas indicator in Table 2 shows that labourers in Gauteng, which includes Johannesburg, the greater Tshwane and Ekurhuleni, along with those in the greater Cape Town, Durban/eThekwini and Nelson Mandela Bay metropolitan areas, earn above average incomes compared to those in the rest of the country.

From the above description of the survey data it is clear that there are interesting differences in the earnings of day labourers in South Africa.To take the analysis a step further, the following section presents the results of regression models of the correlates of earnings.

Empirical analysis

In the econometric model that follows, day labourers' earnings per week 2 are examined as a function of a range of factors.In the analysis, earnings are measured as the natural log of earnings per week.The first two models are similar to Mincerian wage equations.Here age is included since day labouring involves hard physical labour and one would expect that younger, stronger labourers would earn more.The age variable is a dummy where "age under 20 is the comparator category.Education is also a dummy variable where the comparison is with labourers with no schooling.Experience as a day labourer is measured by the experience variable in years.The variable frequency of hire measures the frequency with which the day labourer is hired by the same employer for more than three days.However, this does not mean that those workers are necessarily hired more frequently, thereby introducing a possible implicit endogeneity problem, only that they are hired by the same employer more often.The comparison category is those labourers that never get hired by the same employer more than three times.Typejob is a dummy variable that distinguishes between the two types of jobs identified by cluster analysis.The more skilled cluster-2 jobs are compared to the less skilled cluster-1 jobs.Day labourers typically do more than one job and the variable varietyjob measures the number of jobs that they reported doing as a proportion of the total of twenty job types.The variable fulltimejob is a dummy variable that takes a value of one if the day labourer has ever held a full-time job.The model is estimated by OLS.

Table 3 presents a first round of results.The reported standard errors are robust to heteroskedasticity and the variance inflation factors are all less than 10.Model 1 contains only the age dummies.Compared to the day labourers younger than 20 years, earnings in a good week increase with age.For those older than 45 the coefficients are smaller but still positive (this is also the case for Beta coefficients).The coefficient for the age group 56 to 60 years is negative, which means that this group earns less in a good week compared to the day labourers younger than 20 years.These decreasing returns do not hold for the day labourers older than 60 years, who have a positive coefficient.However, this may be explained by a cross-tabulation of age categories and the type of work by cluster which showed that this is the only group where there are more workers doing skilled work than unskilled work.In model 2 education and experience is added.Though there is a positive relationship between age and earnings, experience in terms of the number of years worked as a day labourer, is negatively related to earnings, but insignificant.This holds true even when the age dummies are not included.

The education dummies have the day labourers with no schooling as the comparator category.It seems that compared to having no schooling, having some primary schooling is negatively associated with earnings.Having completed primary school is positively associated with earnings, but it is insignificant.However, having only some secondary schooling is again negatively associated with earnings, compared to having no schooling.

Source: OLS Regression analysis

There are positive and significant relationships between earnings and completed secondary schooling as well as between earnings and post-school qualifications.This seems to correspond with Fourie's (2011) observation that education level is positively and significantly associated with employment only once persons have a matric qualification or higher.

Note that once education is included the negative relationship between earnings and the age group 56 to 60 years changes, but is insignificant.

Version 3 of the model is extended further through the inclusion of the frequency of hire dummies.Compared to those that are never hired by the same employer, day labourers that are often hired by the same employer for more than three days earn more.There is a negative relationship between earnings and being seldom hired by the same employer, compared to those that are never hired by the same employer.Model 4 is the most complete model and also includes the typejob, varietyjob and fulltimejob variables.Doing jobs in the skilled cluster is positively associated with earnings.Table 3 shows that there is a positive and significant relationship between earnings in a good week and doing more jobs.Having held a full-time job at some stage is also positively and significantly associated with earnings.Model 4 explains approximately 29 per cent of the variance of earnings in a good week.

Model 5 in Table 3 is an approximation of the more typical Mincerian form of the wage equation.The age dummies are replaced by the category midpoints in years and an agesquared term is calculated.The number of years of education is approximated in the same fashion.Experience is measured in years and a squared term is also added here.Experience in this case does not refer to age minus education minus six years, but merely the number of years a person has been working as a day labourer.The correlation between age and experience would be relatively low in this case.This allows one to include them in the same model.The rest of the model remains as in version 4. This does not seem to change the results substantively.The age-squared and experience-squared terms have coefficients of zero and the other relationships remain practically unchanged.

A key argument of this paper is about where the day labourers are.It isargued that large urban areas do allow for a better match between workers and jobs, and this allows day labourers to become more specialised.The data that are available precludes the estimation of spatial wage equations (see, for example, Garretsen, Schramm, & Brakman's ( 2003) Helpman-Hanson model), but there are a number of ways to test whether location matters.To do this, the above model 4 was supplemented with explanatory variables.At the most basic level it is possible to add controls for location.Model 6 below includes measures of the thickness of the labour market.The metro dummy indicates whether the day labourer works in a metropolitan city or not.The location of the day labourers can be identified at district council level and thus population density can be included as a measure of agglomeration.The data are from Global insight's Regional Economic Explorer database.A measure of occupation density was also constructed.This measures the number of day labourers per type of work (skilled or unskilled) per district council, for each of the respondents.Greater occupation density means more people doing the type of work you are doing, where you are doing it.For all three of these variables the theory in section 2 would predict a positive relationship with earnings in a good week.To test the claims that a thick labour market allows for better matching and specialisation, it is also possible to examine some interactions.Model 7 below includes a number of interactions: metro*typejob, metro* varietyjob, metro*occudensity, typejob*occuden-sity and typejob*varietyjob.Again, the reported standard errors are robust to heteroskedasticity and the variance inflation factors are all less than 10.

The results of model 6 show that the location variables add significantly to the explanatory power of the model.The results are similar to that of model 4 above, save for the fact that experience, or the years worked as a day labourer, is now positively (if insignificantly) associated with earnings.The metro dummy is positive and significantly related to earnings.Unfortunately the coefficient of the population density variable is practically zero, but greater occupation density is positively and significantly associated with earnings.These can be interpreted as the change in the log of earnings in a good week for a one standard deviation change in the particular independent variable.The benefit of standardised betas is that they allow for comparison of coefficients.This means that the largest positive relationships with earnings in a good week are with working in a metropolitan area, doing skilled work, being hired by the same employer more often and doing a greater variety of jobs.However, doing a greater variety of jobs is only better for unskilled workers as skilled workers are better off specialising.In this model, working in a metropolitan area and being hired by the same employer more often are more important than education.The largest negative relationship with earnings in a good week is with the competition from other workers in metropolitan areas.

To check the robustness of the results, the same models were estimated to explain the difference in earnings between a good and a bad week and also only the earnings in a bad week.The results were broadly similar and are not reported here.

Conclusions and recommendations

This paper examined the employment of day labourers across South Africa to establish whether the thickness of the labour market determines earnings.The key claims to test were whether large urban areas allow for a better match between workers and jobs, whether it allows for day labourers to become more specialised and if these factors contribute to higher earnings.The regression models examined location as one of the correlates of earnings while controlling for a range of individual specific characteristics of day labourers.

It is important to keep the limitations of the analysis in mind.Since only a single crosssection of data is available it is not possible to control for unobserved heterogeneity as one would in panel data models.The results cannot speak to causality, but it is possible to examine the direction of relationships and to determine how much of the variance of the dependent variable is explained by the independent variables.If it were the case that more able workers select themselves into the larger urban areas, these results over-estimate the importance of agglomeration.This possible upward bias in the coefficient of the metro dummy is however ameliorated by the results of the other interaction terms which support the notion that the thicker metropolitan labour market allows workers to become more specialised and receive higher earnings.Furthermore, the interviews with the day labourers, in terms of their origin, suggest a general migration from poorer provinces to the wealthier economic powerhouse provinces such as the Western Cape and Gauteng.The aim is to improve their chances of being hired as day labourers and earn higher levels of income for their services.This migration is not limited to the more skilled day labourers, but is a general demographic feature of the sample population.

The results show that education is positively associated with earnings once workers have a matric qualification, and all the workers who have completed vocational training receive earnings above the average.Higher skilled jobs are also positively related to earnings.Years of experience working as a day labourer do not seem to contribute to earnings, but having had a full-time job at one time does contribute to earnings.There was some evidence of the thickness of the labour market's association with earnings.Throughout, the day labourers who were hired by the same employer more often received higher earnings.This is indicative of a better match between workers and jobs that increases earnings.Of course there is the possibility that it also captures unobserved effects such as ability or commitment.There was a positive relationship between earnings in a good week and doing more jobs.Labourers seemed to benefit from diversification rather than specialisation.However, when the metropolitan areas dummy is interacted with variety the results favour specialisation, and diversifying into doing more jobs is negatively associated with earnings in a good week.Thus it seems that the thicker metropolitan labour market allows workers to become more specialised and, therefore, to be more efficient.The increased efficiency is positively associated with workers' wages.Throughout, the dummy for metropolitan areas was positive and significant.The conclusion is that the thickness of the labour market matters for day labourers.

Though this conclusion may seem obvious, the implications are not.More often than not, analyses of employment and unemployment in South Africa conclude with calls for the development of people, with emphasis on the importance of education and training.When it comes to the informal sector, issues such as labour market institutions, regulation and access to training and finance are mentioned.The results here have shown that education, vocational training and the ability to do higher skilled jobs are positively associated with earnings in the day labour market of the informal economy of South Africa.However, it is also clear that these advantages are better leveraged in the thick labour markets offered by urban agglomerations.This has significant implications for spatial development.The 2009 World Development Report stated that markets shape the economic landscape, but spatially targeted interventions tend to dominate policy discussions.The report argues that in the face of market forces, such interventions tend to be inefficient.Policymakers should rather focus on creating and supporting spatially blind institutions and spatially connective infrastructure (World Bank, 2009).For South Africa this all means more rapid urbanisation and a need to facilitate the mobility of people.Urban transformation, infrastructure development and service delivery raise a host of challenges beyond the labour market.

Endnotes 1 The authors would like to thank an anonymous ERSA referee, two anonymous referees of SAJEMS as well as participants at ERSA's 2011 Public Economics workshop for their helpful comments on earlier versions of the paper.The authors wish to acknowledge Economic Research Southern Africa (ERSA) for financial assistance with this research paper.All errors and omissions remain our own.2 Day labourers have to contend with low and variable levels of income as well as highly irregular hiring patterns (Blaauw, 2010).The data reveals that the variance in the distribution is not as pronounced for weekly income as it was for the monthly income of day labourers in Pretoria in 2004 (Blaauw et al., 2006:267).This guided the authors to make use of weekly income for the analysis.The income in a good week is the best possible scenario for the day labourers and therefore used in the present analysis.

Figure 2
2

Figure 3
3
Figure3shows the day labourers' highest qualification level obtained and the vocational

Figure 3
3
Figure 3 Education and training

Table 1
1
The type of job
FrequencyValid percentAverage earningsPCA grouping

Table 2
2
Means of earnings in a good week, in Rand
MeanMeanAgeProvinceAge group: under 20271 Gauteng413Age group: 21-25373 Mpumalanga366Age group: 26-30397 KwaZulu-Natal415Age group: 31-35410 Eastern Cape346Age group: 36-40390 Limpopo137Age group: 41-45411 North West318Age group: 46-50333 Free State214Age group: 51-55365 Northern Cape250Age group: 56-60288 Western Cape572Age group: over 60382LocationQualificationMetropolitan areas477No schooling379 Everywhere else371Some primary schooling314Frequency of employmentCompleted primary school367 Hired by same employer: Often644Some secondary schooling362 Hired by same employer: Seldom479Completed secondary school543 Hired by same employer: Sometimes266Post-school qualification547 Hired by same employer: Never366Employment historyType work by clusterHave held a full-time job348 Unskilled314Have never held a full-time job422 Skilled485Source: Survey data

Table 3
3
Regression results: Explaining earnings in a good week
Dependent variable: log of earnings in a good weekModel 1Model 2Model 3Model 4Model 5(Constant)5.4435.4875.5215.255(.079)(.092)(.087)(.099)Age dummy 21-184.108.40.206.117(.084)*(.082)(.072)*(.071)Age dummy 26-30.290.246.257.228(.083)*(.081)*(.072)*(.071)*Age dummy 31-35.320.317.295.265(.085)*(.082)*(.073)*(.072)*Age dummy 36-40.253.299.246.221(.087)*(.084)*(.075)*(.074)*Age dummy 41-45.239.300.249.232(.089)*(.087)*(.077)*(.077)*Age dummy 46-50.067.161.171.163(.095)(.093)(.083)*(.082)*Age dummy 51-55.198.284.222.213(.108)(.106)*(.094)*(.094)*Age dummy 56-60-.054.073.100.107(-.131)(.129)(.114)(.113)Age dummy over 60.187.257.146.102(.230)(.223)(.198)(.196)Age approximation.033(.088)*Age approximation squared.000(.000)Education: Some primary schooling-.233-.159-.154(.057)*(.051)*(.050)*Education: Completed primary schooling.063.094.088(.065)(.058)(.057)Education: Some secondary schooling-.088-.010-.020(.055)(.049)(.048)Education: Completed secondary schooling.384.362.325(.062)*(.055)*(.054)*Education: Post-school qualification.399.465.416(.104)*(.092)*(.091)*Education years approximation.034(.004)*Years worked as a day labourer-.005-.003-.002-.007(.003)(.003)(.003)(.004)*Years worked squared.000(.000)Frequency of hire dummy: Often.454.399.400(.046)*(.045)*(.046)*Frequency of hire dummy: Sometimes.223.177.160(.042)*(.041)*(.042)*Frequency of hire dummy: Seldom-.390-.404-.438(.039)*(.039)*(.039)*Type work: Skilled cluster=1.207.213(.022)*(.023)*Variety of day labour jobs.673.737(.101)*(.102)*Ever held a full time job =1.081.080(.024)*(.024)*Adjusted R-squared.009.073.271.297.279F-stat4.54419.15229.59669.949120.696n34353435343534353415* = significant at the 5% level

Table 4
4
Regression results: Location and earnings in a good week
Dependent variable: log of earnings in a good weekModel 6Model 7Beta coefficients(Constant)5.0504.968(.093)(.093)Age dummy 21-25.149.138.074(.066)*(.065)*Age dummy 26-188.8.131.52(.066)*(.065)*Age dummy 31-22.214.171.124(.067)*(.066)*Age dummy 36-40.209.187.085(.069)*(.068)*Age dummy 41-45.225.195.076(.071)(.071)*Age dummy 46-50.196.166.053(.077)*(.076)*Age dummy 51-55.261.224.051(.087)*(.086)*Age dummy 56-60.198.183.030(.105)(.104)Age dummy over 60.227.221.017(.182)(.179)Edu: Completed secondary schooling.151.136.064(.051)*(.051)*Edu: Post-school qualification.092.098.018(.086)(.085)Years worked as a day labourer.003.005.028(.002)(.002)Frequency of hire dummy: Often.379.355.166(.042)*(.042)*Frequency of hire dummy: Sometimes.198.192.109(.039)*(.038)*Frequency of hire dummy: Seldom-.336-.351-.234(.036)*(.036)*Type work: Skilled cluster=1.063.071.219(.021)*(.044)*Variety of day labour jobs.207.335.199(.095)*(.142)*Ever held a full time job =1.7111.360.047(.022)*(.022)*Metro areas =1.068.745.319(.033)*(.125)*Population density.000.000.031(.000)(.000)Occupation density4.5564.758.279(.618)*(.066)*Metro areas * Type job.028.008(.066)Metro areas *Variety job-.952-.061(.401)*Metro areas * Occupation density-8.814-.257(1.380)*Type job * Occupation density1.135.053(.473)*Type job * Variety job-1.071-.168(.187)*Adjusted R-squared.394.410.410F-Stat93.96083.35183.351n341134113411* = significant at the 5% levelSource: OLS Regression analysis
Appendix AThe appendix shows the results of the principle component analysis.Varimax rotation was used with Kaizer normalisation.The extracted components explain 46 per cent of the variance of the different types of jobs.
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The carbon brace

Jean-Claude Bernard
Cyril Lecante
Julie Deceuninck
Gregory Notin
Lydie Journoud
Frederic Barral
The carbon brace
R E S E A R C H Open Access
Background: The CMCR brace (Corset MonocoqueCarbone respectant la Respiration -which means Monoshell Carbon Brace respecting Breathing) is an innovative brace, used in orthopaedic treatment for progressive thoracic, thoraco-lumbar or combined scoliosis, whatever their etiology. It can be used at the very young age without disrupting the chest growth, but should be kept for reducible scoliosis in older teenagers.Brace description and principles: The CMCR brace is monoshell while retaining the corrective principle of the polyvalve Lyon brace with one or two supports (brace "pads") located on hump(s).In contrast to Lyon brace made of plexidur and structured by metal reinforcement with adjustable but fixed localized supports, the CMCR brace is made of polyethylene and carbon with adjustable and mobile supports. This mobility provides a permanent pressure, which varies depending on ribs and spine movements. The correction is obtained without spinal extension so that each respiratory movement takes part in a gradual return to dorsal kyphosis. Results: Results were presented in two published analysis:• In the first retrospective study about 115 patients, French-published in the Annals of Physical Medicine and Rehabilitation (2005), the CMCR brace stabilized moderate scoliosis, decreased the vital capacity (VC) of 13% compared to the VC without brace, and did not have sufficient impact on the hump reduction. Treatment had better results when started at Risser 3 or 4 than Risser 0, 1, 2. The brace was then modified to increase the dorsal pad pressure and the location of correction forces was defined more precisely through the use of 3D analysis.• The second study published in Scoliosis (2011) mainly focused on the impact on VC at brace setting up and followed a cohort of 90 patients treated with CMCR. Girls as well as boys increased VC during treatment, and at brace definitive removal, VC had increased of 21% from the initial value, whereas the theoretical VC at the same time rose by 18%.The difference between the time where the child actually wears its brace and the time asked by the clinician for the brace to be worn is only 1 hour, which means that this brace is accepted by teenagers.Conclusions: Orthopaedic treatment is still a heavy treatment for teenagers in growth period. This orthosis is designed to partly maintain spine and chest mobility. We hope so to have part in improving life conditions of these teenagers, compared to those treated with rigid braces.

Introduction

Idiopathic scoliosis affects 2 to 3% of the population, including 0.3 to 0.5% with a scoliosis over than 20°. The Lyon treatment is applied since the 1950s for the conservative treatment in scoliosis over 30°and comes in 2 phases:

Correction by 1 or 2 successive casts (Abbott plaster cast) made in EDF framework and worn 45 days each Then adaptation of a Lyon brace, worn to bone maturity.

As we had to deal with earlier treatment of scoliosis, where clinical and radiological deformations are less expanded, we began to understand a bit more its evolution and were lead to develop corrective orthosis that suit to moderate scoliosis [1]. Currently available braces have demonstrated a real efficiency but still present disadvantages because of their rigidity, especially for the thoracic function that is limited by the lack of expansion while breathing in.

The purpose of this paper is to present the CMCR brace (Corset Monocoque Carbone respectant la Respirationwhich means Monoshell Carbon Brace respecting Breathing).

Scoliosis that present only a lumbar component will not be considered in the brace panoply of this work.

History

At the end of the 50's, Pierre STAGNARA finalized his modernization and streamlining of Adolescent Idiopathic Scoliosis treatments, at Les Massues hospital. It was the time of « Lyon school » and the Lyon brace was born.

Scoliosis screening nowadays occurs earlier. Orthopaedic treatments by brace have to adapt to these lower angle deformations.

Braces should have minimal impact on these young children lives, while remaining effective on curves correction. Braces have to take into account new needs, such as comfort, lightness, aesthetic, preservation of respiratory capacity and overall respect for the child growth.

From the meeting of these new settings is born the CMCR. This monoshell brace was developed by Lecante society at the Centre des Massues [2] in Lyon in 1997, under the aegis of Dr. Bernard. Inspired by the location of the Lyon brace supports, the rigid pads are changed into mobile ones in the CMCR brace. It calls upon new materials, more efficient (x-rays transparent, dynamic. . .) but also more comfortable. Thus, results on scoliosis curves remain optimal without interfering with thoracic growth, and lie on a greater participation of the child, which is the key to the treatment success.

Theoretical principles

How the brace might work (theory)

The CMCR is a light brace reinforced by carbon blades and implemented without prior casting.

The CMCR design is based on clinical and radiological data (Cobb angles, pelvic parameters, spinal 3D analysis): they allow us to give the right direction to the force(s) implemented in the brace to correct the scoliosis torsion. To this correction force will be opposed two counter forces, to obtain a 3-points effect. It is possible to use the extension component of the CMCR, offered by the monoshell structure of the brace, by adjusting the under-axillary supports.

In a recent work [3] we have been able to show the interest of this brace, through the appropriate use of carbon material, for the rib cage development and for the respiratory capacity of these children treated with CMCR during many years, at the time where the thoracic growth is the highest.

General description of the mechanical principles of correction

The CMCR originality lies in the appropriate use of prestressed carbon to create support forces on brace pad(s). This support keeps some mobility during movements, and especially in respiratory ones. Correction is thus permanent; the child cannot escape the support, as it is the case with rigid orthosis. The thorax mobility is preserved, sparing at best the subject breathing. Dorsal and lumbar pads can be adapted tailored to the desired correction, and considering the 3 plans. The brace will be individualized regarding curve type, subject age and weight, trying to get the best compromise for the patient, throughout treatment.

The classification used for prescription

The treated group is made of 90% girls and 10% boys (sex ratio) which corresponds to the usual prevalence data in the literature about scoliosis (Figure 1).

The CMCR is implemented at 12 years on average; a little younger in boys (11 years) than in girls (12 years).

It is generally worn for progressive scoliosis with a Cobb angle from 20 to 30°, but can be implemented in some other cases, taking into account the 3D analysis [4], patient age and sitting size, and curve(s) reducibility.

Variations of the brace according to the curve pattern: description for the 3 kinds of curves treated with CMCR The CMCR is prescribed for combined scoliosis (or double major) in more than 73% of cases. Thoraco-lumbar scoliosis represents 15%, and finally 10% of thoracic ones.

This sharing out is not due to any technical specificity of the brace, but corresponds to the percentages of scoliosis various forms in our everyday practice. We need to state that no lumbar scoliosis is treated with CMCR, because we use another orthosis (3-points brace) for this kind of scoliosis.

Combined scoliosis: the brace is equipped with two mobile pads.

One pad on the dorsal deformity: after 3D analysis, the orientation of the support force corrects the torsion, with a maximal orientation ¾ anteroposterior when the torsion is maximal. Prestressed carbon of the mobile pad allows by its elasticity the inspiratory movements and promotes the expiratory ones. One pad on the lumbar deformity: the support force of this pad is diametrically opposed to the thoracic one to facilitate spinal detorsion. If needed, this lumbar pad will render some lordosis by pressing on vertebrae transverse apophysis ( Figure 2).

Thoracic scoliosis: the brace is equipped with only one pad on the dorsal deformity, associated with two counter-supports; one superior under-axillary countersupport on the opposite side to the thoracic curve and another inferior counter-support next to the lumbar column, still opposite to the thoracic curve.  The deformation 3D correction is made by adjusting precisely the location and the pressure of the pad, as explained before.

The pad will be all the more lateral that the torsion is important; in this case, it is no more directly on the hump noticed by clinical examination. The more anterior is the pad, the more necessary it is to put another mobile pad (and not only a simple rigid counter-support) to avoid the lumbar kyphosis.

Adaptation difficulties: the CMCR is sometimes difficult to adapt in high thoracic scoliosis, with a few place for the superior counter-support.

Thoraco-lumbar scoliosis: the brace is equipped with an only pad on the thoraco-lumbar deformity, associated with two rigid counter-supports. Be careful not to disturb the sagittal plane (as can be seen with the hyper corrective brace) as the main pad must allow a dual objective: regain some dorsal kyphosis and some lumbar lordosis. It is only by the 3D analysis that the pad correct orientation can be found and then proved when the brace adaptation is completed.

Brace description

The CMCR is a monoshell brace with an innovative system of mobiles pads. It preserves vital capacity by mobile pressures in thoracic and in lumbar, thanks to use of prestressed carbon. It retains pads from the Lyon brace, but gives more opportunities to orient forces [5].

The basic structure is in polyethylene. There is an anterior opening to allow an easier putting on ( Figure 3).

Three strengthening pieces of Kydex (KYDEX sheet is an acrylic-polyvinyl chloride composite produced by KYDEX, LLC. Engineered for thermoforming fabrication, KYDEX sheet, combines the advantageous properties of both the acrylic and the polyvinyl chloride components. From acrylic, it obtains superior rigidity and formability; from PVC, outstanding toughness, chemical resistance and good interior finish ratings) plasticstiffen this shell: one medial posterior that stiffens the sagittal plane and two lateral ones that set in addition the carbon blade.

The Main shell

Lumbar pad: (if needed) (Figures 4 & 5)

It is independent of the main shell and provides lateral translation. The pressure of the pad is lateral and paravertebral (to correct lumbar rotation and to maintain lumbar lordosis).

The carbon blade is the link between the brace and the pad (slipped under the lateral reinforcement and fixed on it).

This attachment device allows variations of strength and/or location of the pad.

Thoracic or thoraco-lumbar pad

This shell is also independent and is built like the lumbar pad ( Figure 6). Its position has to be lateral and a bit    posterior, to allow the thoracic spine to stay in kyphosis and avoid the flat back.

The carbon blade is the link between the brace and the pad; its suppleness allows rib cage movements for a good breathing. (It is slanted to follow the ribs inclination).

This attachment device allows variations of strength and/or location of the pad.

Carbon blades

These blades are made of carbon fibre braids (mainly unidirectional).Their thickness, determined by the number of layers, gives the searched flexibility according to every type of patients.

The carbon blade is prestressed and keeps pressure during exhalation.

Fastening systems

The main system of opening and closing is a flexible rack at chondro-costal awnings level to maintain a constant clamping. Velcros at manubrial and pelvis levels complete it.

Finishing touches

Foam is added on pressure area and sub axillary. A leather flap is placed on the opening of the brace, between the two polyethylene parts.

Pratical issues

How to prescribe the brace: principles of correction written in prescriptions by MDs

The CMCR is prescribed after a clinical and radiological examination of the patient. The prescription takes into account patient age, scoliosis progression and deformity reducibility. Here is the standard prescription form for a combined scoliosis:

CMCR brace for combined scoliosis right thoracic/ left lumbar with:

∘ Right dorsal pad T5-T12. Specify the orientation that should be given to the pad: ¾ posterior or lateral. ∘ Left lumbar pad T12-L4. Specify the orientation that should be given to the pad: postero-anterior or lateral. ∘ Rigid left sub-axillary counter-support. How to build the brace: principles of construction by CPOs, with some photos; (see also the discussion regarding brace pressure above Optical acquisition

Lecante society uses since 1997 ORTEN W system for the manufacture of CMCR (Figure 7). This is an optical 3D image acquisition method for the trunk, and a Conception et Fabrication Assistée par Ordinateur (CFAO) software (Cad cam system) for the rectified positive [6,7,8].

The sensor consists in a portico of 2 meters side square in the center of which the patient is placed. 4 CDD camera recorders are symmetrically distributed in 4 columns, as well as 8 structured light projectors that project alternatively black and white fringes on the patient. The deformation of these fringes allows the calculation of the bust outer surface.

The acquisition is completed within less than 2 seconds (which allows an optimal posture).

Its accuracy is of the order of one millimeter.

Positioning the patient

The subject is covered with a white tubular slinky jersey ( Figure 8).

It is then placed at the center of the sensor, elbows apart and hands forward at shoulder height, on two vertical stands.

This position is checked on the computer screen and can be modified prior to the optical print acquisition (Figures 9 & 10).

Rectifying the positive

The optical acquired data are then rectified on computer by the orthotist, in the same way as for a plaster positive (Figure 11).

At this stage we realize the brace final form with expansion areas and pressure areas on deformities, as well as the creation of the waist that will be the brace base).

Data is then sent to a milling machine that carves the positive in polyurethane foam ( Figure 12).

Thermoforming the trial brace

Thermoforming of polyethylene (PE) is made at 160°by manual draping on the foam positive. The welding of PE plate is made on the front part of the positive (since the opening of the brace is anterior). The PE cools all night long, and the brace is removed from the positive the next morning.

Fitting

This molded trial brace is then put on the patient, as if it were the final brace (it should not be too big not to hurt the patient, and should allow to keep a precise vision of the definitive brace). It is maintained closed with tape. Fitting helps to:

Control volumes adaptation Define the cutting on different sides of the brace : anterior (chest), superior (clavicles), and inferior (in the groin) Determine the location of the pads (with help of radiological and clinical examination)  Determine the place of carbon blades as well as the power that will be applied on pads (depending on the thickness and the width of the blade) Determine where the Kydex W reinforcements should be placed Precise the position of the expansion areas Notice potential painful points ( Figure 13)

Finishing touches

Brace and pads are cut ( Figure 14). We realize then 3 Kydex W reinforcements (a posterior one and 2 side ones), which are coupled to the brace by rivets.

Carbon blades and pads are then assembled ( Figure 15).

Brace delivery

Still checking radiography, the orthotist puts the brace on the child who wears a cotton seamless shirt. He makes sure that the brace is well adapted, with all parts on the right height. The fitting depends on the scoliosis importance and reducibility. The child should

How to check the brace: principles of checking by MDs and CPOs

Before starting treatment, the patient and its parents receive oral and written explanations on the kind of brace and on the different steps of its manufacture and adaptation.

To be enlightened before making the choice of treatment, the patient receives as well oral and written information about inconvenience that might occur during treatment (as for example cutaneous irritation, sleeping troubles, constriction feeling. . .) and means to prevent it.

CMCR-wearing patients and their parents benefit throughout treatment from a therapeutic education to be able to manage treatment by themselves.

The child is seen every morning during one week to adapt brace, adjust carbon pressure, and improve comfort and quality of life in orthosis.

A front/profile radiography is done at the late brace adaptation to control its effectiveness (especially to        confirm that all supports are well-oriented and at the right height). This x-ray is compared to x-ray without brace as well as face x-ray with partial suspension [9,10].

In the making and at the brace delivery, simple explanation is given to get the child and its parents understand how the brace works.

Fitting tips: indelible marks are put on brace straps to help along. Tips to put on and off the brace without help, which is part of the therapeutic education: either in a standing position or in a lying one. Cleaning tips: brace is worn on a seamless T-Shirt that should be changed every day. Brace has to be washed with soap once a week.

In case of technical problem: manufacturer and referent physiotherapist at Les Massues can be joined by phone. Address and telephone number of the fabricant workshops are given, depending on where the patient lives, to correct technical problems if necessary.

Protocols: description of the protocols generally used according to each clinical situations; (see criteria for bracing) Three months after brace adaptation, the patient is first seen by the referent physiotherapist at Les Massues, who assesses how the brace is physically and psychologically tolerated, how respiratory capacity, height and weight evolve. The patient benefits then  from a clinical examination by the senior physician doctor (codified clinical examination without brace) and meets afterward the orthotist. All this controls are carried out in a multidisciplinary united consultation at day hospital. After 6 months of brace wearing, these controls are made again besides a face/profile naked standing radiography which is compared to the initial one.

Successive checking is made every 6 months with naked face radiography.

The brace renewal is proposed when growth no longer allows a correct adaptation of the orthosis (cutaneous or bone conflicts impossible to resolve). We cannot adapt the distance between pelvic girdle and sub-axillary supports which is an advantage of Lyon brace.

A synthetic form of clinical and radiological patient data ("spine sheet") is regularly supplemented to have an insight into scoliosis evolution at a glance.

Everyday usage: the number of hours per day that the patient will wear the brace During pubertal growth period, brace is worn on average 20-21 hours out of 24, with permission to take it off for sport practice at school and outside school.

When the peak of pubertal growth has gone away (at least 18 months after the first menstrual period), and if the improvement is stabilized concerning weight and sitting height, a gradual removal is started. . .until a night wearing the last 6 months of treatment. At that time, sitting height, standing height and weight are stable since about one year.

Before the pubertal growth and if scoliosis is moderate and supple (less than 25°), brace will not be worn at school but will be worn around 18 hours from school end until the next morning.

Results

This study is retrospective among 321 patients treated in our department, which explains that the group is made of 321 patients at the beginning of the study, but of only 90 patients at the end of the study, because only 90 patients at that time had completed the treatment [3,11,12] ( Table 1).  At the definitive brace removal, all kinds of scoliosis are stabilized by the orthosis and VC has increased. One may infer that the patient presents at the end of treatment a low residual deformity, which is unlikely to keep on getting worse in adulthood.

Case reports

Discussion

Later in this work we compare the group treated with CMCR to a group of patients treated with Lyon brace [13]. The characteristics of the scoliotic group treated with Lyon brace are presented in the table below about 240 patients. Kinds of scoliosis are similar to the CMCR group (Table 2).

Lyon brace is used later that CMCR to treat scoliosis: 2 years later on average in girls and 3 years later on average in boys.

Cobb angle at the beginning of treatment is 10°more on average in Lyon brace compared to CMCR; VC without brace is reduced by 28% from the theoretical VC (Table 3).

At the final removal of Lyon brace, curves are stabilized. However, residual Cobb angle is over 30°, which means that scoliosis will have to be regularly controlled, even in adulthood, to make sure that scoliosis evolution will not continue ( Table 4).

As shown by the table below, VC decreases less at the CMCR setting up (−0.3) than at the Lyon brace setting up (−0.5) and this difference is significant.

At definitive brace removal, VC has more increased in CMCR (0.4 liter on average) than in Lyon brace (0.3 liter on average) but this difference is not significant.

The Lyon brace setting up must be preceded by a reduction by Abbott plaster to reduce curve importance. Scoliosis treated by CMCR are generally less pronounced; however it can happen that in our daily practice we begin treatment with a scoliosis reduction cast, followed by a CMCR if the obtained correction is sufficient to be maintained by CMCR carbon supports.

The Lyon treatment can only be started around puberty whereas CMCR can be used whatever the age.

This leads us to propose several kinds of brace (CMCR, Milwaukee brace, Lyon brace, hyper-correcting brace) for our scoliotic patients to make a choice depending on patient age, importance of scoliosis. . . It is not possible to treat all kinds of scoliosis with an only brace.

Conclusion

CMCR brace is innovative for several reasons:

The use of prestressed carbon corrects deformity without blocking chest movements and thus preserves respiratory capacity in brace. The scoliosis correction is progressive through the use of mobile supports which can always be adapted to the stiffness areas appearing throughout growth. Radiological analysis with 3D reconstruction is used before brace design and at the late adaptation to get an optimal scoliosis correction by using minimal support forces.

3D analysis of scoliosis is essential to allow a gradual return to a harmonious cervical, dorsal and lumbar profile.

It has been demonstrated that CMCR brace allows a better quality of life than Lyon brace [14,15]. Orthopaedic treatment is still a heavy treatment for adolescents in growth period; this orthosis is designed to preserve partly spine and chest mobility.

We hope so to have part in improving life conditions of these teenagers, compared to those treated with rigid braces.

Figure 1
1Diagram for brace indications regarding age and Cobb angle.

Figure 2
2Localization of pressure.

Figure 3
3Three kydex support pieces; 2 side ones, and 1 posterior.

Figure 4
4Front view of the main shell.

Figure 5 Figure 6
56Left Right thoracic pad.

Figure 7
7Three-dimensional scanning unit (ORTEN optical sensor).

Figure 8
8Patient positioning during optical print acquisition. ∘ Control of the chondro-costal awnings, with kyphosis effect if necessary.

Figure 9
9Fringe used for the 3D thorax reconstruction.

Figure 10 Figure 11
10113D Milling different steps in rectifying positive.

Figure 12
12Numerically controlled milling machine.

Figure 13
13Fitting thepolyethylene shell.

Figure 14
14Posterior and front views of the shell after fitting.

not be too embarrassed by its brace, and especially the sitting position should be paid attention to.

Figure 15
15Different steps in CMCR assembly.

Figure 16
16Physical therapy training in CMCR.

Figure 17
17Face and profile x-rays without brace. Thoraco-lumbar scoliosis.

Figure 18
18CMCR with right thoraco-lumbar pad.

Figure 19
19Face and profile x-raysin CMCR.

Figure 20
20Face and profile x-rays without brace. Double-major scoliosis.

Figure 21
21CMCR with right thoracic pad and left lumbar pad.

Figure 22
22Face and profile x-raysin CMCR.

Exercises: specific exercises while in the brace (if any), with photos of how to perform themGetting aware of deformity (Figure 16) Breathing work: getting aware of abdominal and diaphragmatic breathing, fight against restrictive syndrome Trying to get more spinal mobility: asymmetric exercises to open concavity(ies) and ilio-lumbar angle (stretching), fight against the increase of sagittal deformities (erasing or accentuation of curves), active axial self-extension (symmetrical stretching and muscles developing in long position) Harmonization of anterior and posterior muscles: spinal muscles developing in long position, abdominal strengthening (chondro-costal awnings, pelvic tilt, . . .)Upkeep of sub-pelvic extensibility and musculature: upkeep of sub-pelvic muscles extensibility (growth), strengthening exercises to compensate for the lack of mobility caused by the orthosis First sight of relaxation

Table 1
1Characteristics of the population at the beginning of treatment with CMCR brace and at its definitive removalVariable
Group at the beginning of treatment
Group at the definitive brace removal

Gender
Girls
289 (90%)
Girls
86 (95%)

Boys
32 (10%)
Boys
4 (5%)

Mean age
Girls
12 years 3 months
Girls
16 years

Boys
11 years 1 month
Boys
15 years 5 months

Curvature type

Double-major
234 (72,9%)
Double-major
69 (76%)

Lumbar
7 (2,2%)
Lumbar
-

Thoracic
31 (9,7%)
Thoracic
7 (8%)

Thoraco-lumbar
49 (15,3%)
Thoraco-lumbar
14 (16%)

Cobb angle

Double-major
21,7°Double-major
17,6°T

horacic
23,6°Thoracic
18,1°T

horaco-lumbar
24,1°Thoraco-lumbar
20,2°S

keletalmaturity

Risser 0
152 (48,4%)

Achieved

Risser 1
65 (20,7%)

Risser 2
42 (13,4%)

Risser 3
36 (11,5%)

Risser 4
19 (6,1%)

Theoretical Vital Capacity (VC)
Girls
3,4 l.
Girls
3,5 l.

Boys
3,5 l.
Boys
4,2 l.

Forced Vital Capacity (FVC)

Girls
2,4 l.
Girls
2,7 l.

Boys
2,7 l.
Boys
3,6 l.

Table 2
2Characteristics of the population at the beginning of treatment with Lyon braceVariable
Group
n
Percentage

Gender
Girls
184
76,7%

Boys
56
23,3%

Kind of scoliosis

Double-major
157
65,4%

Lumbar
2
0,8%

Thoracic
35
14,6%

Thoraco-lumbar
40
16,7%

Triple-curved
6
2,5%

Risser

0
58
42,3%

1
21
15,3%

2
21
15,3%

3
16
11,7%

4
13
9,5%

5
8
5,8%

Table 3
3Characteristics of the population at the beginning of treatment with Lyon brace and at its definitive removalVariableGroup Mean at the beginning of treatment Mean at the definitive brace removalAge
Girls
13 years 3 months
15 years 7 months

Boys
14 years 7 months
16 years

Cobb angle

Double-major
35,5°/30,1°31,4°/27,1°T

horacic
35,5°32,6°T

horaco-lumbar
33,9°31,8°T

heoretical VC
Girls
3,3 l.
3,8 l.

Boys
4 l.
4,1 l.

FVC

Girls
2,4 l.
2,7 l.

Boys
3,1 l.
3 l.

Table 4
4Comparative study -Impact of the brace kind on evolution of FVC (forced vital capacity) FVC evolution at brace definitive removal compared to the beginning of treatment (liters)Indicator

Case n°1: Alice 12 years old Thoraco-lumbar curve T6L2 30°right T6L2 6°right in brace(Figures 17,18 & 19)Case n°2: Camille 13 years old
Double major T4T11 28°right T11L4 29°left
In brace: T4T11 21°right T11L4 13°left (Figures 20,21 & 22)

http://www.scoliosisjournal.com/content/8/1/3
3Technician Ortho Prothesist, Lyon, France.4Physiotherapist, CMCR des Massues Croix Rouge française, Lyon, France.Competing interestNo conflict of interest.ConsentThe patients who participated in this work and, in particular, the patients shown in the iconography gave their written agreement as well as their parents.Ethical approvalThis study was approved by the Ethics Committee of the Massues' Center-Croix-Rouge française.
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The carbon brace. Bernard, Scoliosis. 83Cite this article asCite this article as: Bernard et al.: The carbon brace. Scoliosis 2013 8:3.