Department Physiotherapy, Faculty of Medicine, Espinardo Campus, University of Murcia, Murcia, 30100, Spain

Department of Physiotherapy, University of Murcia, Murcia, Spain

Department of Basic Psychology and Methodology, University of Murcia, Murcia, Spain

Abstract

Background

Low back pain (LBP) is common in children and adolescents, and it is becoming a public health concern. In recent years there has been a considerable increase in research studies that examine the prevalence of LBP in this population, but studies exhibit great variability in the prevalence rates reported. The purpose of this research was to examine, by means of a meta-analytic investigation, the prevalence rates of LBP in children and adolescents.

Methods

Studies were located from computerized databases (ISI Web of Knowledge, MedLine, PEDro, IME, LILACS, and CINAHL) and other sources. The search period extended to April 2011. To be included in the meta-analysis, studies had to report a prevalence rate (whether point, period or lifetime prevalence) of LBP in children and/or adolescents (≤ 18 years old). Two independent researchers coded the moderator variables of the studies, and extracted the prevalence rates. Separate meta-analyses were carried out for the different types of prevalence in order to avoid dependence problems. In each meta-analysis, a random-effects model was assumed to carry out the statistical analyses.

Results

A total of 59 articles fulfilled the selection criteria. The mean point prevalence obtained from 10 studies was 0.120 (95% CI: 0.09 and 0.159). The mean period prevalence at 12 months obtained from 13 studies was 0.336 (95% CI: 0.269 and 0.410), whereas the mean period prevalence at one week obtained from six studies was 0.177 (95% CI: 0.124 and 0.247). The mean lifetime prevalence obtained from 30 studies was 0.399 (95% CI: 0.342 and 0.459). Lifetime prevalence exhibited a positive, statistically significant relationship with the mean age of the participants in the samples and with the publication year of the studies.

Conclusions

The most recent studies showed higher prevalence rates than the oldest ones, and studies with a better methodology exhibited higher lifetime prevalence rates than studies that were methodologically poor. Future studies should report more information regarding the definition of LBP and there is a need to improve the methodological quality of studies.

Background

The term low back pain (LBP) was defined by Andersson

LBP often begins in childhood, and in adolescents the prevalence is similar to that of adults

In recent years there has been a considerable increase in research studies that examine the prevalence of LBP in this population

This variability found in the prevalence estimates may be due to differences among the studies in such factors as the age of the sample, the sample size, the definition of LBP, the LBP recall period, the strategy for extracting data and the methodology used.

The prevalence of a condition is the number of cases in a specified population at a particular time

According to the literature on the epidemiology of LBP in children and adolescents, the prevalence rates increase with the age of the subjects

Several narrative reviews have been published about the prevalence of LBP in children and adolescents

Based on the results of previous research, several hypotheses were raised: (a) the mean estimate of point prevalence will be lower than that of period prevalence and, in turn, this will be lower than that of lifetime prevalence; (b) the prevalence rates will increase with the age of the participants in the samples, and (c) females will present higher prevalence rates than males.

Methods

In order to accomplish our objectives, a systematic review and a meta-analysis were carried out on observational studies that reported prevalence rates of LBP in children and/or adolescents.

Selection criteria of the studies

To be included in the meta-analysis, the studies had to meet the following criteria: (a) the study must be an observational study (survey research, longitudinal or cross-sectional design) that reports any prevalence rate of low back pain in children and/or adolescents (≤ 18 years old); (b) the sample size had to have at least 50 participants; (c) studies had to be carried out between 1980 and April of 2011, as previous literature searches carried out by our research team evidenced an absence of studies that report LBP prevalence rates for children/adolescents before 1980; (d) studies had to be written in English, French, Italian, Spanish, or Portuguese; (e) studies could be published or unpublished. Cohort, case–control, controlled clinical trials, and randomized clinical trials were excluded, as they report incidence rates instead of prevalence rates.

Literature search

To locate studies that met the selection criteria, several literature searching strategies were used. Firstly, the following electronic databases were consulted: ISI Web of Knowledge, MedLine, PEDro, IME, LILACS, and CINAHL. The search period extended to April 2011, with the Medical Subject Headings: adolescents, children, childhood, back pain, low back pain, spinal pain, epidemiology, and prevalence. Secondly, several electronic specialized journals were consulted such as,

Two reviewers independently: (a) screened the title and abstract of each reference to locate potentially relevant studies, and once hardcopies of the screened papers were obtained, (b) reviewed them in detail to identify articles that fulfilled the selection criteria.

The total number of references identified with all of the searching strategies used was 2,272, of which 2,188 were excluded in a first screening. The main reasons for deleting these studies were because the participants in the samples were adults (about 55%), the studies did not report prevalence rates (about 20%), the studies were clinical trials (about 15%), or other reasons (about 10%). The searching process enabled us to select 59 articles that met the selection criteria, with a total sample size of 125,483 participants. Figure

Flow chart of the selection of studies for the meta-analysis.

**Flow chart of the selection of studies for the meta-analysis.**

Data extraction

With the purpose of identifying characteristics of the studies that may affect the prevalence rates estimated, a codebook was produced that included a series of potential moderator variables of the prevalence rates of LBP. The study characteristics were classified into substantive (subject and context variables), methodological, and extrinsic variables

The following subject characteristics were coded: (a) the origin of the sample (school, community, university, or sport origin); (b) the mean age of the sample (in years), and (c) the gender distribution of the sample (percentage of males). Two context characteristics were coded: the continent and the country where the study was carried out.

The following methodological characteristics were coded: (a) the initial sample size of the study; (b) the final sample size (subjects actually used to calculate the prevalence rate); (c) the response rate (percentage of people in the final sample divided by the number of people in the initial sample); (d) the study design (longitudinal

**Methodological criteria of epidemiological studies.**

Click here for file

To assess the reliability of the coding process, two researchers independently coded 14 studies randomly selected from the total set of studies (24%). The inconsistencies between the two coders were solved by consensus, and when these were due to ambiguity in the codebook, this was corrected. The codebook can be obtained from the corresponding author upon request. To assess the coding reliability, intra-class and kappa coefficients were calculated for the continuous and categorical variables, respectively. On average, the intra-class correlation was 0.994 (range: 0.98 - 1.0), and the kappa coefficient was 0.989 (range: 0.77 - 1.0), all of which can be considered to be highly satisfactory

Prevalence rates

Three types of prevalence were included in our review: point, period, and lifetime prevalence. In turn, period prevalence was classified according to the specific period of time reported in the study (one and two weeks, 1, 3, 6, and 12 months). From each study, at least one prevalence rate could be obtained. When a study applied a longitudinal design, only the prevalence rate at the beginning of the study was recorded in our meta-analysis. To assess the reliability in the calculations of the prevalence rates, the same 14 studies used to assess the coding reliability of the moderator variables were used. The mean intra-class correlation was 0.999 (range: 0.996 – 1.0), which was highly satisfactory

Statistical analysis

As each study could report more than one prevalence rate (e.g., point and lifetime prevalences), separate meta-analyses were carried out for the different types of prevalence in order to avoid dependence problems. To normalize the distribution of the prevalence rates, these were transformed by means of the logit event rate: ^{
LP
}/(^{
LP
} + 1), with

In each meta-analysis, a random-effects model was assumed to calculate a mean prevalence rate and a 95% confidence interval

The heterogeneity of the prevalence rates was assessed with the ^{2} index. When the number of prevalence estimates was large enough (20 or more studies), a forest plot was constructed. In order to test whether publication bias might be a threat to the validity of the prevalence estimates, funnel plots were constructed and Duval and Tweedie’s trim-and-fill method was applied

When the ^{2} index exhibited a large value (over 25%), then analyses of potential moderator variables were carried out. However, due to the small number of studies, these analyses were applied only for the lifetime prevalence rate, as this was reported in 30 studies. The analyses of moderator variables were carried out by assuming a mixed-effects model. For the categorical moderator variables, weighted ANOVAs were calculated, with the _{B} statistic assessing the statistical significance of the moderator variable on the prevalence rates, and the _{W} statistic assessing the model misspecification. For the continuous moderators, weighted simple meta-regressions were applied, with the _{R} statistic testing the statistical significance of the moderator variable, and the _{E} statistic assessing the model misspecification. In all of the moderator analyses, the proportion of variance accounted for by the moderator variable, ^{2}, was calculated following Raudenbush’s proposal

The statistical analyses were carried out with the meta-analysis program Comprehensive Meta-analysis 2.0

**PRISMA Checklist.**

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Results

Descriptive characteristics of the studies

Fifty-nine articles fulfilled the selection criteria

**Characteristics of the studies presenting LBP prevalence data used in this meta-analysis.**

Click here for file

The sample size distribution was very skewed, with a median of 622 subjects and minimum and maximum values of 88

Three subject characteristics were coded: the origin of the sample, the mean age, and the percentage of males in the sample. Most of the samples were recruited from schools (46 studies; 78%), followed by the community (7 studies, 11.9%). On average, the mean age of the samples was 13.6 years old (range: 9–18.4) and the mean percentage of males was 51.1% (range: 41.5% – 100%).

With regards to the methodological variables, the mean response rate was 83.8%, and most of the studies used a cross-sectional design (52 studies, 88.1%). The data extraction method most commonly used was the questionnaire (46 studies, 78%), followed by the questionnaire and physical examination combined (5 studies, 8.5%), the interview (4 studies, 6.8%), the questionnaire and interview combined (2 studies, 3.4%), and the interview and physical examination combined (2 studies, 3.4%).

Out of the different types of prevalence, period prevalence was the most commonly reported (25 studies, 42.4%), followed by the lifetime and period prevalence combined (15 studies, 25.4%), the lifetime prevalence alone (eight studies, 13.5%), the lifetime, period, and point prevalences combined (five studies, 8.5%), the lifetime and point prevalences combined (three studies, 5.1%), the point prevalence alone (two studies, 3.4%), and the period and point prevalences combined (one study, 1.7%).

The methodological quality scores of the included studies are reported in Additional file

**Methodological Quality of the 59 epidemiological studies.**

Click here for file

For the first block of methodological questions concerning the sample representativeness (questions 1, 2 and 3 of Additional file

In relation to questions related to the quality of the data (questions 4, 5, 6, 7, 8 and 9 of Additional file

To collect the data, the studies used different instruments, such as questionnaires (79.7%), interviews (8.5%), and examinations (11.9%). The instruments had to be validated or at least its reliability had to be tested.

With regards to the definition of LBP (questions 10, 11 and 12 of Additional file

Mean prevalence and heterogeneity testing

Table ^{2}). The mean point prevalence obtained from 10 studies was 0.120 (95% confidence limits: 0.09 and 0.159). As expected, period and lifetime prevalence rates were higher than point prevalence. Thus, the mean period prevalence at 12 months obtained from 13 studies was 0.336 (95% confidence limits: 0.269 and 0.410), whereas the mean period prevalence at one week obtained from six studies was 0.177 (95% confidence limits: 0.124 and 0.247). The mean lifetime prevalence obtained from 30 studies was 0.399 (95% confidence limits: 0.342 and 0.459). Figure

**Type of prevalence**

**
k
**

**
N
**

**
Min.
**

**
Max.
**

**
p
**

**95%**

**C. I.**

**
Q
**

**
df
**

**
I
**

**
p
**

**
p
**

* _{+}: mean prevalence. _{l} and _{u}: lower and upper confidence limits of the 95% confidence interval around the mean prevalence. ^{2}: heterogeneity index.

Point prevalence

10

49,124

0.032

0.350

0.120

0.090

0.159

546.87*

9

98.3

Period prevalence:

1 week

6

9,812

0.097

0.350

0.177

0.124

0.247

156.56*

5

96.8

2 weeks

1

1,193

0.246

0.246

0.246

0.222

0.271

--

--

--

1 month

14

23,191

0.025

0.398

0.183

0.128

0.255

1618.85*

13

99.2

3 months

2

4,126

0.224

0.513

0.355

0.134

0.662

187.49*

1

99.5

6 months

7

25,037

0.008

0.420

0.177

0.088

0.324

2197.00*

6

99.7

12 months

13

19,673

0.174

0.603

0.336

0.269

0.410

997.00*

12

98.8

Lifetime prevalence

30

61,732

0.086

0.648

0.399

0.342

0.459

4957.79*

29

99.4

Forest plot of the lifetime prevalence rates. _{l} and _{u}: lower and upper confidence limits of the 95% confidence interval around the mean prevalence rate.

**Forest plot of the lifetime prevalence rates.**_{l} and _{u}: lower and upper confidence limits of the 95% confidence interval around the mean prevalence rate. The last row in the figure presents the mean prevalence assuming a random-effects model.

For all of the types of prevalence, the heterogeneity ^{2} indices were over 95% (see Table

Analysis of publication bias

Out of the 30 studies that reported lifetime prevalence estimates, 29 of them were published studies. In order to check whether publication bias might be biasing the estimated mean prevalence, a funnel plot was constructed, as presented in Figure

Funnel plot of the lifetime prevalence logits.

**Funnel plot of the lifetime prevalence logits.** The three full circles are imputed logits by means of the Duval and Tweedie’s trim-and-fill method.

Similar analyses were carried out for the other types of prevalence that were represented in the meta-analysis with at least 10 prevalence estimates. This was the case for point prevalence and for one and 12 months period prevalences. Point prevalence exhibited a funnel plot that was very close to symmetry, and only one new prevalence rate had to be imputed to the 10 original prevalence estimates to adjust the funnel plot to symmetry, leading to original (_{+} = 0.120) and adjusted (_{+adj} = 0.103) mean point prevalences that were very similar. With regards to one month period prevalence, the trim-and-fill method did not have to imput any new prevalence rates to achieve symmetry in the funnel plot. On the contrary, the 12 month period prevalence needed to add five new prevalence rates on the left side of the funnel plot to achieve symmetry, leading to a clear decrease in the mean prevalence from 0.336 (with the 13 original prevalence rates) to 0.245 (when imputing five new prevalence rates to the original ones). Therefore, although the point and one month period prevalences do not seem to be affected by publication bias, the 12 month period prevalence showed an overestimation of the population prevalence rate.

Analyzing moderator variables

As mentioned above, the analysis of moderator variables was carried out for the lifetime prevalence rates only, as the other types of prevalence were represented in the meta-analysis with a small number of estimates (under 20). Tables

**Moderator variable**

**
k
**

**
p
**

**95%**

**C. I.**

**ANOVA results**

**
p
**

**
p
**

_{+}: mean prevalence. _{l} and _{u}: lower and upper confidence limits of the 95% confidence interval around the mean prevalence. _{B}: between-categories statistic to test the influence of the moderator variable on the prevalence rates. _{W}: within-categories statistic to test the model misspecification. ^{2}: proportion of variance accounted for by the moderator variable.

Europe

21

0.390

0.314

0.472

_{B}(4) = 1.95, ^{2} = 0.0

North America

3

0.455

0.255

0.670

_{W}(25) = 4227.25,

Oceania

1

0.403

0.128

0.757

Africa

2

0.277

0.114

0.532

Asia

3

0.490

0.285

0.698

School

25

0.398

0.333

0.467

_{B}(3) = 0.87, ^{2} = 0.0

Community

2

0.396

0.197

0.638

_{W}(26) = 3833.03,

University

2

0.470

0.249

0.703

School + sport

1

0.280

0.085

0.619

Questionnaire

23

0.411

0.354

0.471

_{B}(1) = 0.36, ^{2} = 0.143

Interview

4

0.365

0.243

0.507

_{W}(25) = 2345.19,

**Moderator variable**

**
k
**

**
b
**

**
Q
**

**
p
**

**
Q
**

**
p
**

**
R
**

_{j}: regression coefficient of the moderator variable. _{R}: statistic to test the influence of the moderator variable on the prevalence rates. _{E}: statistic to test the model misspecification. ^{2}: proportion of variance accounted for by the moderator variable.

Mean age (years)

30

0.104

5.10

.024

2017.26

< .001

0.457

Gender (% of males)

27

0.008

0.34

.557

4819.51

< .001

0.0

Response rate

27

−0.023

2.94

.086

4807.91

< .001

0.0

Quality scale (0–100)

30

0.019

6.21

.013

2886.94

< .001

0.348

Publication year

30

0.062

9.82

.002

4957.61

< .001

0.0

Dispersion diagram of the simple meta-regression of the mean age of the subjects and the logit prevalence rates.

**Dispersion diagram of the simple meta-regression of the mean age of the subjects and the logit prevalence rates.**

The continent where the study had been carried out did not affect prevalence rates (Table

Several methodological variables were also coded in order to examine their potential influence on the prevalence rates. Thus, the data extraction method did not show a statistical relationship with the prevalence rates (Table _{+} = 0.411) giving slightly higher prevalence rates than the interviews (_{+} = 0.365). The response rate did not show a statistical relationship with the prevalence rates (Table

Table ^{2} = 0.676), with higher prevalence rates when the study described the non response. The other one was whether the study clearly defined the specific area of pain (^{2} = 0.376), with higher prevalence rates in the studies with a clear specification of the area of pain.

**Quality item**

**
k
**

**
p
**

**95%**

**C. I.**

**ANOVA results**

**
p
**

**
p
**

_{+}: mean prevalence. _{l} and _{u}: lower and upper confidence limits of the 95% confidence interval around the mean prevalence. _{B}: between-categories statistic to test the influence of the moderator variable on the prevalence rates. _{W}: within-categories statistic to test the model misspecification. ^{2}: proportion of variance accounted for by the moderator variable. Five of the 12 quality items were not included in the table due to one of their categories being represented by one study only or by none (survey designed for studying prevalence rates, data collection was uniform, validated interview, validated exam, and memory period clear).

Yes

21

0.416

0.346

0.489

_{B}(1) = 0.77, ^{2} = 0.0

No

9

0.358

0.260

0.469

_{W}(28) = 4942.26,

Yes

5

0.486

0.401

0.572

_{B}(1) = 4.42, ^{2} = 0.676

No

20

0.384

0.343

0.427

_{W}(23) = 1162.44,

Yes

27

0.403

0.343

0.467

_{B}(1) = 0.21, ^{2} = 0.0

No

3

0.358

0.202

0.551

_{W}(28) = 4910.99,

Yes

26

0.411

0.344

0.480

_{B}(1) = 0.87, ^{2} = 0.0

No

4

0.326

0.190

0.498

_{W}(28) = 4853.39,

Yes

26

0.400

0.339

0.464

_{B}(1) = 1.32, ^{2} = 0.015

No

3

0.517

0.332

0.698

_{W}(27) = 4754.11,

Yes

20

0.472

0.413

0.532

_{B}(1) = 17.98, ^{2} = 0.376

No

10

0.266

0.205

0.338

_{W}(28) = 2192.08,

Questionnaire

16

0.399

0.316

0.487

_{B}(1) = 0.00, ^{2} = 0.0

Interview

14

0.399

0.311

0.494

_{W}(28) = 4635.79,

An explanatory model

Several substantive and methodological characteristics of the studies showed a statistical relationship with the lifetime prevalence rates, so a multiple regression model can offer a predictive model of the expected prevalence under certain conditions. The predictor variables included in the model were the mean age of the participants in the sample, the publication year, and two methodological variables: the total score on the quality scale (0–100) and the quality item “delimitation of pain” (Yes, 1; No, 0). As shown in Table ^{2} = 0.438). Two of the four predictive variables showed a statistically significant relationship with the prevalence rates once the other predictors were controlled: the delimitation of pain (

**Predictor variable**

**
b
**

**
Z
**

**
p
**

**Results of the full model**

_{j}: partial regression coefficient of each moderator variable. _{R}: statistic to test the statistical significance of the full model. _{E}: statistic to test the model misspecification. ^{2}: proportion of variance accounted for by the moderator variables.

Constant

−80.160

−2.49

.013

Delimitation of pain

−0.516

−2.05

.041

_{R}(4) = 27.24,

Mean age (years)

0.029

0.55

.584

^{2} = 0.438

Quality scale (0–100)

0.005

0.63

.531

_{E}(25) = 1306.02,

Publication year

0.040

2.49

.013

Discussion

The aim of this research was to examine, by means of a meta-analytic investigation, the prevalence rates of LBP in children and adolescents, as well as to search for characteristics of the studies that can explain the heterogeneity exhibited by the prevalence rates. With this purpose, a total of 59 studies fulfilled our selection criteria and were included in our meta-analysis.

The results confirmed the hypothesis that the lifetime prevalence is higher than the period prevalence and, in turn this is higher than the point prevalence. These results coincide with those obtained by Louw et al.

The hypothesis that the prevalence rate would increase with the age of the participants in the samples was confirmed by our results. These findings are in line with those obtained by Balagué et al.

With regards to gender, authors such as Shebad et al.

The large heterogeneity found in all types of prevalence indicates the existence of characteristics of the studies causing this variability. The publication year influenced the lifetime prevalence rates, with the higher prevalence rates being reported in the most recent studies. This result seems to be very solid, as in the multiple meta-regression model publication year was one of the two predictors that achieved a statistically significant relationship with the lifetime prevalence, once controlled the methodological quality of the studies, the delimitation of pain, and the mean age of the sample. However, what our analyses do not enable us to determine are the reasons of that increase in the prevalence rates. Thus, it could be that children are changing their activity level or they are more overweight; it could be that the actual prevalence has not changed but the reporting has; or it could be that the questions used to assess the prevalence have changed. This point would need more research. Regarding the methodological quality of the studies, the studies with a better quality tended to show higher lifetime prevalence rates than studies that were methodologically poor.

The most common methodological shortcomings of the studies included in the review were the lack of a clear definition and delimitation of LBP and the absence of important specifications of LBP such as the frequency of episodes, its intensity and duration. In particular, out of the studies published between 1980 and 2001, only 40.9% reported a clear definition of LBP, whereas in the most recent studies (from 2002 to date) this percentage was 73%. With regards to the LBP specifications, the percentage was 71% for studies published in the last 10 years and 29% for those that were not published in the last 10 years.

Limitations of the meta-analysis

It is important to note some limitations of our meta-analysis. The small number of studies that reported point and period prevalence rates discouraged the analysis of moderator variables and, as a consequence, this kind of analysis was applied for lifetime prevalence rates only. On the other hand, the absence of a more detailed description in the primary studies about such important aspects as the exact area of pain caused uncertainty in our coding process.

Implications for clinical practice

The results of our meta-analysis have important consequences for professionals. Our finding of higher prevalence rates in the most recent studies suggests that LBP is a problem that is increasing in childhood and adolescence. As a consequence, more attention should be devoted to develop and apply prevention programs for young children in order to break this trend. On the other hand, our finding of higher prevalence rates in the studies with older subjects points to the need for efforts towards an early detection of LBP in children and adolescents.

Implications for future research

Our results enable us to make recommendations for future research in this field. Firstly, it is advisable that future studies report more information regarding the definition of LBP. Issues relating to the exact area of pain, the frequency of episodes, their intensity, and the duration need to be specified. Secondly, there is a need to improve the methodological quality of studies in order to avoid threats against the representativeness of the samples and the internal validity of the studies. Finally, studies should report prevalence rates of LBP disaggregated by age and sex.

Conclusion

In conclusion, the most recent studies seem to show higher prevalence rates than the oldest ones, and studies with a better methodology tend to show higher lifetime prevalence rates than studies that are methodologically poor.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

All authors contributed to the conception and design, acquisition, analysis and interpretation of data and drafting of the manuscript. AGC and JSM participated in the critical revision of the manuscript for important intellectual content. ICM and JSM performed the statistical analyses. All authors read and approved the final manuscript.

Acknowledgements

No funding was received for this study.

Pre-publication history

The pre-publication history for this paper can be accessed here: