Global,Regional,and National Burden of Neck Pain in Young Population,1990–2021: An Age–Period–Cohort Analysis and Projections to 2050 Based on the Global Burden of Disease Study 2021

Abstract

Study Design

Eco-epidemiological study.

Objective

Analysis the spatial-temporal trends in neck pain burden among young people at global, regional, and national levels.

Methods

Data on neck pain among youth from 1990 to 2021 was sourced from the Global Burden Disease (GBD) 2021 database. This research delineated the evolving trends in neck pain burden by comparing various regions and timeframes, employing the age-period-cohort (APC) model to assess the factors effects on neck pain burden. The Autoregressive Integrated Moving Average (ARIMA) model was utilized to forecast the global burden of neck pain among youth by 2050s.

Results

Although the global burden of neck pain shows a steady development trend, there is strong heterogeneity among regions. The burden was more severe in the females and high-middle Socio-Demographic Index (SDI) region. By APC model, the burden was found to increase with age, and the period effect showed an initial upward trend followed by a decline and rise final, although the relative risk remained above 1. The cohort effect indicated that the relative risks for global, higher SDI, initially decreased before rising, while the relative risks for low-middle SDI and low SDI regions have continued to increase over the years. Predictive modeling showed by 2050, the number of youth suffering from neck pain will continue.

Conclusions

Neck pain remains an important health problem and poses a global public health challenge in the future, requiring prevention and control targeting key populations and regions.

Keywords

neck pain young population age-period-cohort model global burden disease

Introduction

Neck pain is defined as discomfort experienced between the upper boundary of the neck and the spinous process of the first thoracic vertebra, which may radiate to the head, trunk, and upper limbs.¹ Not only is the impact of neck pain on quality of life substantial, it is also a warning sign for a variety of serious conditions, such as severe myelopathy, atlantoaxial subluxation, and metastasis.² Various factors contribute to neck pain, including prolonged poor posture, overuse of the cervical spine, and improper sleeping positions, etc. It is estimated that nearly 60-80% people will experience neck pain at some point in their lives,³ and the incidence of neck pain within a 1-year period ranges from approximately 10.4% to 21.3%.⁴ Moreover, nearly 50% of people will endure some degree of recurring or frequent neck pain, which is recognized as a serious public health issue.⁵

Most patients suffering from neck pain experience various physical impairments, including decreased neck mobility, headaches, and carotid artery dissection, and neck pain is also a common cause of stroke in individuals under 50 years of age.⁶ With chronic neck pain developing, both economic and medical costs escalate in correlation with the severity of the condition.⁷ In terms of prevalence and years lost due to disability, neck pain ranks among the top 5 chronic pain conditions.⁵ In 2016, low back pain and neck pain were ranked maximum in U.S. healthcare spending among 154 medical conditions. Notably, with the advancement of science and technology, there is a concerning trend of neck pain occurring at younger ages, particularly among young individuals who are in a critical phase of physical development and growth.⁸ The teenage years represent a sensitive period for the emergence of musculoskeletal issues,⁹ which may persist into adulthood and adversely affect future health.

While relevant studies have explored the global neck pain burden, they have primarily focused on individuals of all ages and have not specifically addressed the burden of neck pain among young people.¹⁴ Since the GBD database includes data on neck pain across various age groups, this study aims to analyze the burden of neck pain in youth globally utilizing the GBD 2021 database. The current will categorize the global youth population (aged 15-39) into subgroups based on region, gender, and age group. Furthermore, the analysis of neck pain burden will be conducted from the perspectives of age, period, and cohort, with predictions on the prevalence, incidence, and disability adjusted life years (DALYs) associated with neck pain in young people projected through 2050.

Materials and Methods

Data Source

This study used the dataset provided by the GBD 2021 public database (https://ghdx.healthdata.org/gbd-2021/datainput-sources), accessed on October 18, 2024. GBD 2021 represents the most comprehensive and systematic epidemiological study globally, conducted by the Institute for Health Metrics and Evaluation (IHME). It evaluates the burden of disease, encompassing incidence, prevalence, DALYs, etc. In GBD 2021, neck pain is defined as pain occurring in the cervical spine region, with or without accompanying radiating pain to the upper limbs, lasting for a minimum of 24 h. This condition is classified in the International Classification of Diseases, 10th revision (ICD-10), under the code “ M54.2”. Data from GBD 2021 were selected and organized by gender, age, location, and year, which extracted using the Global Health Data Exchange (GHDx) query tool (https://vizhub.healthdata).

Regional data is provided by GBD 2021. Data on the prevalence, incidence and DALYs and corresponding age standardized rates (ASRs) of neck pain from 1990 to 2021 were collected. The SDI is constructed based on national per capita income, average years of education, and the total fertility rate of the population over 20 years old, dividing 204 countries into 5 level: high SDI, high-middle SDI, middle SDI, low-middle SDI, and low SDI. The index ranges from 0 to 1, indicating levels of development from least to most developed.

Statistical Analysis

This study employed ASR and 95% UI, estimated annual percentage change (EAPC) to assess temporal trends in the incidence, prevalence, and DALYs associated with neck pain from 1990 to 2021. ASR enhances the fairness of comparisons between different demographic groups by adjusting the data for varying age distributions. The EAPC serves as a statistical metric to examine trends in public health data, specifically focusing on ASRs over designated time frames. The methodology involves using the year as the independent variable within a logarithmic linear regression model, fitting the natural logarithm of the ASR trend according to the equation y = a + bx + e, where y = ln(ASR), x = calendar year, a = intercept, and e = error term. The EAPC = (exp(β) - 1) × 100, with the confidence interval (CI) for the linear regression model set at 95%. All statistical analyses and graphical representations were conducted using R Studio software (version 4.4.1) along with the appropriate R packages. For all analyses, P values less than 0.05 (two-tailed) were deemed statistically significant.

Age-Period-Cohort (APC) Analysis

The APC model that serves as a multiple regression framework that estimates the impact of factors such as age, period, and cohort on various events is a multidisciplinary statistical method.¹⁰ Collinearity is a common characteristic observed in age-period-cohort models, where cohort is defined as the difference between period and age. The separate effects of age, period, and cohort on disease burden could not be estimated. Therefore, this study avoided this issue by calculating estimable APC parameters and functions, while imposing no constraints on the model parameters. All APC analysis depend on R Studio software (version 4.4.1) and specific methods were referred to previous studies.¹¹

In the APC model, it is essential for the age and period intervals to be equal. Therefore, the age groups of 15-19, 20-24, 25-29, 30-34, and 35-39 are included in the model analysis, with a period interval of 5 years. The selected periods for this study are 1992-1996, 1997-2001, 2002-2006, … , and 2017-2021. Additionally, the cohorts are grouped by the years 1950, 1960, 1970, … , and 2010. National and regional population data on neck pain from the GBD 2021 were incorporated into the model, and analysis was conducted. Relative risk (RR) and 95% CIs are used to elucidate the age, period and cohort effects on prevalence, incidence, and DALYs. When the RR value is more than 1, it suggests that the factor increases the risk of prevalence, incidence and DALYs of neck pain. When the RR value is less than 1, it suggests that the factor decreases the risk of prevalence, incidence and DALYs of neck pain.

Autoregressive Integrated Moving Average (ARIMA) Model

The ARIMA model is widely employed in the fields of epidemiology and public health for predicting disease incidence. This statistical model, designed for time series data analysis, effectively captures data trends. The fundamental premise of the ARIMA model is to forecast future values based on historical data.¹² This study compiled data on the prevalence, incidence and DALYs associated with neck pain from 1990 to 2021 to project neck pain burden from 2022 to 2050.¹³

Results

Global, Regional and National Trends in Prevalence, Incidence and DALYs of Neck Pain in Young Population

Globally, neck pain accounted for 62 842 852 (95% UI: 42 044 118 to 82 561 925) prevalent cases and 15 432 908 (95% UI: 10 228 999 to 21 177 214) incident cases, leading to 6 416 702 (95% CI: 3 830 146 to 9 790 460) DALYs in 2021 (Table 1). Moreover, the ASRs of prevalence, incidence, and DALYs for neck pain in 2021 were 2443.02 (95% UI: 1923.04 to 3002.33), 519.28 (95% UI: 407.85 to 633.38) and 242.3 (95% UI: 162.6 to 342.76), respectively (Table 1). Global young population neck pain cases rose with total population growth. From 1990 to 2021, prevalence, incidence, and DALYs remained relatively stable (Table 1).

Table 1.

The Number, ASR and EAPC of Prevalence, Incidence, DALYS of Neck Pain Globally and Regionally in 1990 and 2021.

	Global		High SDI		High- Middle SDI		Middle SDI		Low-Middle SDI		Low SDI
	1990	2021	1990	2021	1990	2021	1990	2021	1990	2021	1990	2021
Prevalences number (N, 95% UI)	45 688 866 (30 791 655 to 60 518 224)	62 842 852 (42 044 118 to 82 561 925)	8 778 382 (5 867 688 to 11 571 752)	9 204 744 (6 179 055 to 12 116 211)	10 469 331 (7 089 118 to 13 739 822)	10 466 866 (6 959 849 to 14 037 384)	15 425 332 (10 396 696 to 20 517 716)	20 403 022 (13 524 477 to 27 172 907)	7 629 124 (5 181 491 to 10 204 188)	14 344 746 (9 614 963 to 19 051 825)	3 340 756 (2 278 319 to 4 444 936)	8 368 711 (5 711 773 to 11 129 851)
ASPR (per 100 000, 95% UI)	2436.71 (1912.98 to 2992.64)	2443.02 (1923.04 to 3002.33)	2565.37 (2003.12 to 3146.75)	2563.57 (2015.55 to 3136.62)	2636.94 (2084.35 to 3233.63)	2641.01 (2071.81 to 3239.16)	2489.39 (1949.85 to 3061.53)	2531.39 (1987.91 to 3107.99)	2084.52 (1641.98 to 2564.16)	2130.82 (1676 to 2620.14)	2279.1 (1785.4 to 2808.56)	2321.64 (1815.89 to 2866.18)
Estimated annual percentage change 1990-2021 (N, 95% CI)	−0.05 (−0.12 to 0.03)		−0.11 (−0.19 to −0.02)		−0.01 (−0.05 to 0.04)		0.03 (−0.03 to 0.09)		−0.06 (−0.22 to 0.1)		−0.02 (−0.12 to 0.09)
Incidences number (N, 95% UI)	11 298 711 (7 539 952 to 15 409 757)	15 432 908 (10 228 999 to 21 177 214)	1 922 157 (1 270 026 to 2 639 933)	2 014 013 (1 334 424 to 2 747 985)	2 575 656 (1 707 070 to 3 527 626)	2 531 263 (1 662 822 to 3 541 426)	3 992 957 (2 649 448 to 5 444 799)	5 123 997 (3 358 249 to 7 065 955)	1 943 990 (1 308 114 to 2 626 118)	3 615 505 (2 413 821 to 4 924 071)	852 965 (573 278 to 1 147 960)	2 135 066 (1 436 681 to 2 873 735)
ASIR (per 100 000, 95% UI)	513.21 (404.32 to 630.08)	519.28 (407.85 to 633.38)	497.96 (393.38 to 608.71)	505.17 (400.77 to 615.55)	552.85 (436.45 to 681.3)	560.27 (440.25 to 683.62)	550.57 (433.48 to 677.66)	555.25 (437.18 to 679.26)	455.22 (357.31 to 555.35)	463.48 (363.79 to 565.81)	486.26 (381.32 to 595.73)	494.71 (387.89 to 607.47)
Estimated annual percentage change 1990-2021 (N, 95% CI)	0 (−0.07 to 0.07)		−0.03 (−0.11 to 0.05)		0.04 (0.01 to 0.07)		0.01 (−0.05 to 0.06)		−0.06 (−0.21 to 0.1)		−0.01 (−0.11 to 0.09)
DALYs number (N, 95% UI)	4 672 337 (2 800 837 to 7 234 231)	6 416 702 (3 830 146 to 9 790 460)	897 338 (539 295 to 1 385 848)	937 258 (563 952 to 1 431 510)	1 074 680 (650 019 to 1 661 972)	1 073 767 (634 714 to 1 647 240)	1 582 126 (943 254 to 2 455 385)	2 087 798 (1 242 322 to 3 203 831)	775 900 (463 591 to 1 198 705)	1 461 455 (870 693 to 2 248 681)	337 592 (203 549 to 519 968)	850 826 (511 003 to 1 307 686)
Age-standardized DALYs (per 100 000, 95% UI)	241.96 (162.05 to 343.53)	242.3 (162.6 to 342.76)	255.97 (171.06 to 363.01)	255.14 (170.37 to 359.98)	262.58 (177.1 to 370.43)	263.13 (176.5 to 373.8)	247.56 (165.52 to 352.76)	251.3 (168.07 to 356.55)	205.26 (136.11 to 290.95)	210.09 (139.27 to 298.06)	223.57 (148.66 to 317.01)	228.84 (151.86 to 325.01)
Estimated annual percentage change 1990-2021 (N, 95% CI)	−0.04 (−0.12 to 0.03)		−0.11 (−0.19 to −0.03)		0 (−0.05 to 0.05)		0.03 (−0.03 to 0.09)		−0.05 (−0.21 to 0.11)		0.01 (−0.09 to 0.11)

Abbreviation: ASR, age-standardized rate; EAPC, estimated annual percentage; DALYs, disability-adjusted life years; UI, uncertainty interval; CI, confidence interval.

At the regional level, the ASRs of prevalence, incidence, and DALYs for neck pain varied significantly across regions (Supplemental Table 1). In 2021, the top 3 regions in terms of ASR for prevalence were Northern Africa and Middle East (3753.21, 95% UI: 2933.61 to 4686.42), Western Sahara (3225.94, 95% UI: 2523.85 to 4024.13), and Western Europe (2976.49, 95% UI: 2309.97 to 3625.13) (Supplemental Table 1). Moreover, North Africa and Middle East and Western Sub-Saharan Africa ranked top 2 regarding the ASRs of incidence and DALYs. The ASRs of prevalence, incidence, DALYs for neck pain were the lowest in all 3 regions, namely Australasia, South Asia and Southern Latin America. From 1990 to 2021, Western Sub-Saharan Africa experienced the largest increase in prevalence and incidence, while East Asia showed the largest increase in DALYs. Notably, high-income North America displayed the opposite trends in terms of prevalence, incidence and DALYs (Supplemental Table 1).

At the national level, Figures 1 and 2 & Supplemental Figure 1 illustrated the ASRs and EAPC for prevalence, incidence and DALYs across 204 countries in 2021. The largest ASRs for prevalence, incidence and DALYs were observed in Iran, while the opposite was observed in New Zealand (Supplemental Table 2). China showed the largest growing for prevalence, while Kuwait represented the largest increase for incidence and DALYs (Supplemental Table 2). It was worth mentioning that Spain showed the reverse trends for prevalence, incidence and DALYs of neck pain (Supplemental Table 2).

Figure 1.

(A) The ASR for prevalence of neck pain in 204 countries and territories in 2021. (B) The EAPC of prevalence of neck pain in 204 countries and territories from 1990 to 2021. Abbreviation: ASR, age-standardized rate; EAPC, estimated annual percentage change.

Figure 2.

(A) The ASR for incidence of neck pain in 204 countries and territories in 2021. (B) The EAPC of incidence of neck pain in 204 countries and territories from 1990 to 2021. Abbreviation: ASR, age-standardized rate; EAPC, estimated annual percentage change.

Temporal Trends in Neck Pain Prevalence, Incidence and DALYs in Young Population Across Different Age, Sex and SDI Groups

Figure 3 & Supplemental Table 3 showed the temporal trends of neck pain related burden by age, gender and SDI levels. The prevalence, incidence and DALYs for neck pain showed a downward trend in all age groups, while the highest ASRs occurred in the 35-39 age group (Supplemental Table 3). Females consistently exhibited higher ASRs for prevalence, incidence and DALYs compared to males throughout the study period (Figure 3 & Supplemental Table 4). From 1990 to 2021, the ASR of incidence demonstrated a rising trend in countries with high-middle SDI, which also had the highest ASRs for prevalence, incidence and DALYs in 2021. Conversely, the downward trend was observed in countries with high SDI in terms of prevalence and DALYs (Figure 3). The relationship between ASRs and SDI levels across 21 GBD regions was showed in Supplemental Figure 2, which revealed the negative correlation between SDI level and incidence (r = −0.089, P = .025).

Figure 3.

(A) Comparison of gender in ASR of prevalence, incidence and DALYs for neck pain from 1990 to 2021. Red lines are both sex, green lines are female, and blue lines are male. (B) Comparison of SDI levels in ASR of prevalence, incidence and DALYs for neck pain from 1990 to 2021. Red lines indicate the high-middle SDI region, light green lines indicate the high SDI region, dark green low-middle SDI region, blue low SDI region, and pink middle SDI region.

APC Analysis of Neck Pain Burden

In terms of age effect for prevalence, the global and 5 SDI regions consistently showed a steady upward trend with age (Figure 4). As for period effect, the prevalence showed a trend of rising and then declining, and continued to rise after reaching the turning point, which occurred between 2010 and 2015 for high SDI and other SDI levels were between 2005 and 2010 (Figure 4). In terms of cohort effect, there was an increasing trend in prevalence in the low-middle SDI and low SDI regions, while it showed a decreasing trend in other SDI regions (Figure 4). Furthermore, APC analysis results showed age, period, and cohort trends in incidence and DALYs were all similar to prevalence (Supplemental Figure 3 and 4).

Figure 4.

Age–period–cohort effect of ASR of prevalence for neck pain. The red graph (first row) shows the prevalence of neck pain with 15-39 years, the blue graph (second row) shows the period RR of neck pain prevalence during 1990 to 2021, and the green graph (third row) shows the RR of neck pain prevalence in the 1950 to 2010 birth cohort. Dots and shaded areas indicate prevalence or ratios and their corresponding 95% CI. Abbreviation: ASR, age-standardized rate; RR, relative risk.

Forecast

The global burden of neck pain in 2050 was projected based on data on prevalence, incidence, and DALYs from 1990 to 2021 (Figure 5). The results suggested that the global burden related to neck pain will continue to rise through 2050, including prevalence, incidence, and DALYs. It was estimated that by 2050, the prevalent cases, incident cases and DALYs of neck pain will rise to 76 890 264.6 (95% UI: 74 453 102.98 to 79 327 426.22), 18 739 738.49 (95% UI: 18 113 603.38 to 19,365,873.6), 7 736 987 (95% UI: 7 432 513 32 to 8 041 460.89), respectively. In addition, in the next 30 years, the ASRs of prevalence, incidence and DALYs show a rapid decline to 2034, and then a slow increase until reaching a relatively stable level in 2050 (prevalence: 2412.32, 95% UI: 2305.53 to 2519.11; incidence: 510.81, 95% UI: 488.87 to 532.76; DALYs: 239.42, 95% UI: 229.61 to 249.22).

Figure 5.

(A) Projection of prevalent cases, incident cases and DALYs of all age to 2050. (B) Projection of ASR for prevalence, incidence, DALYs to 2050. Abbreviation: ASR, age-standardized rate; DALYs, disability-adjusted life years.

Discussion

The results indicated that the neck pain burden increased with age and was much more severe in women than in men. In addition, high-middle SDI region had higher ASRs of prevalence, incidence, and DALYs. APC model further accounted for the effects of age, period and cohort for neck pain burden. Predictive modeling showed continued upward trends in the number of neck pain prevalence, incidence and DALYs among young population by 2050, indicating that the neck pain burden in young population presented a significant challenge to global health, necessitating targeted, region-specific prevention and control strategies.

Neck pain is a prevalent musculoskeletal disorder and one of the leading cause of disability worldwide. There have been previous studies on the global burden of neck pain, but the data used were not updated and the subjects were the whole population.^14,15 However, recent studies have shown that neck pain also occurs frequently in young people, particularly those in high-stress occupations or experiencing daily mental fatigue, highlighting the need to use up-to-date data to describe the global neck pain burden in young people.^16,17 Among young patients with neck pain aged 15 to 39 years, including high school students, college students, and office workers, etc.^18,19 This was also used as a key word to search for relevant data when analyzing the results.

Regarding the highest and lowest ASRs for prevalence, incidence and DALYs of neck pain burden, Iran and New Zealand were the most representative, respectively. Related studies have shown that this may be related to the local dominant industry,²⁰ physical workers had a higher risk of developing neck pain.^21,22 In Iran, where light industry dominates and the garment industry is massively expanding, sewing machine operators need to remain in a bent position for long periods of time, which can cause neck pain.²³ While in New Zealand, most employees work in offices, and many companies offer relatively free work times and locations. At the same time, New Zealand has a relatively complete public medical service system, which explains the relatively light disease burden.

Gender differences in neck pain burden were also analyzed in this study, which found that the prevalence of neck pain in young women consistently exceeded that in young men from 1990 to 2021. This is also in line with the results of previous studies.²⁴ This disparity can be attributed to multiple factors.²⁵ While adverse working conditions play a role in the development of neck pain for both men and women, women appear to be more susceptible to environmental risk factors.²⁶ It may be related to women’s lower levels of physical activity and reduced bone density.^27,28 Moreover, research has shown that women tend to have lower pain thresholds,²⁹ engage in less physical activity, and experience higher levels of mental and psychological stress compared to men, which can activate muscle spindles and lead to painful tension syndromes.^30,31

The relationship between SDI and neck pain burden was also elucidated. From 1990 to 2021, the neck pain burden was highest in high-middle SDI regions, while it was lowest in high SDI regions. The burden of disease associated with neck pain varied greatly between different levels of SDI, influenced by factors such as lifestyle, medical resources, and environmental conditions. Countries with higher SDI tend to have a greater proportion of sedentary mental workers, who often experience limited mobility, potentially leading to neck pain.³² Conversely, in countries with lower SDI, lifestyle factors are more prominently linked to the prevalence of neck pain. Furthermore, regions characterized by higher SDI benefit from improved access to healthcare resources, which can enhance the diagnosis and treatment of neck pain. In contrast, countries with lower SDI may face challenges related to inadequate healthcare infrastructure, resulting in underreporting or mismanagement of neck pain cases.^33,34

Neck pain risk was influenced by biological age, economic developments, and diagnostic changes.³⁵ The burden increased with age and reached a peak between 35 and 39 years old, which may be related to enhanced work and life stress and decreased physical function.³⁶ Overall, although the global period RR of neck pain fluctuated, it consistently remained above 1 from 1990 to 2021, indicating a persistently high risk of neck pain. The period RR for high and high-middle SDI regions fell below 1 after 2010, particularly in the high-middle region, which can be attributed to advancements in technology and the implementation of effective policies. In 2010, the World Health Organization (WHO) proposed the application of robotics in the manufacturing industry, which undoubtedly reduces repetitive neck weight-bearing movements and reduces occupational exposure.³⁷ The period of RR initially declined due to economic and medical advancements; however, it experienced an increase from 2005 to 2015, particularly in low-middle and low SDI regions. This increase can likely be attributed to changing lifestyles, inadequate medical infrastructure, and insufficient management supervision.³⁵ In the early 2000s, economic globalization facilitated the relocation of manufacturing to low and middle SDI countries, resulting in the growth of labor-intensive industries and a rise in jobs that required sustained head-down and fixed neck postures on assembly lines, thereby escalating biomechanical stress on the cervical spine.³⁸ Simultaneously, advancements in information technology led to increased use of electronic products, which caused chronic strain in the posterior cervical muscles of office workers.³⁹ In 2002, the WHO advocated for the development of ergonomic intervention policies in high SDI countries, while low and middle SDI countries continued to prioritize infectious disease control, resulting in musculoskeletal disorders being overlooked on the public health agenda.⁴⁰ Early life behaviors and exposures can also influence the occurrence of neck pain, which explains why the high SDI, high-middle SDI, and middle SDI cohorts born in 1950 face the highest RR.⁴¹ During this period, developed countries entered the mature stage of industrialization, characterized by the widespread adoption of assembly line operations in the manufacturing industry, which led to an increase in repetitive neck loads.³⁸ In regions with high SDI, individuals born after 1980 have benefited from advancements in musculoskeletal rehabilitation techniques and the widespread adoption of evidence-based physiotherapy protocols, resulting in a reduced conversion rate of chronic neck pain. Conversely, in areas with low SDI, the scarcity of primary medical resources leads to a perception of neck pain as a natural consequence of aging, thereby delaying early intervention.⁴² The lack of basic education coverage in low SDI areas limited the space for occupational choice. The 1950-2006 cohort was mostly concentrated in the informal employment sector, such as street vending and family workshops, and lack of ergonomic training led to severe neck strain.⁴³ At the same time, the fragmentation of medical insurance has made the out-of-pocket payment rate of informal employment group as high as 70%, further inhibiting the medical treatment rate.⁴⁴

The ARIMA model showed that the prevalence, incidence and DALYs of neck pain among 15-39 years old would continue to increase by 2050, but the ASRs of prevalence, incidence and DALYs would first increase, then decrease and then continue to increase. The initial increase may be due to smart wearable devices, and the availability of healthcare infrastructure may increase the detection rate of neck pain.⁴⁵ Advances in medicine, population-wide susceptibility genetic testing, and more targeted treatment may lead to a reduction in the number of cases, but this may have a delayed effect due to uneven development around the world.^46-49 However, the specific effects need to be analyzed according to different regions and different populations, and the sensitivity analysis of the key turning points should be carried out to explain the multi-peak phenomenon.

Neck pain is one of the most common musculoskeletal diseases in the world. To alleviate the burden of neck pain, it is necessary to integrate a three-stage systematic strategy of prevention, diagnosis and treatment, and cooperate with researchers, policy makers and clinicians to form a multi-dimensional intervention framework. In the prevention stage, cohort studies should establish a clear understanding of the epidemiology and etiology of neck pain, and then identify high-risk groups. The government should formulate and supervise the implementation of prevention and control guidelines for neck pain, and increase attention to it. Clinicians should pay attention to early screening and formulate prevention programs based on patients living habits. In the diagnosis stage, both precision and standardization should be emphasized. Researchers should positively explore the molecular markers and radiomics features of neck pain and construct diagnostic classification criteria based on multimodal data. The government should improve the medical insurance payment system, cover early diagnosis technology, and standardize the hierarchical medical pathway. Doctors should strictly follow the evidence-based medicine guidelines, adopt a stepwise diagnostic process, give priority to exclude serious pathological factors, strengthen multidisciplinary cooperation, and solve difficult and miscellaneous diseases. In the treatment stage, researchers need to verify the long-term efficacy of various therapies through RCT experiments, establish prognostic prediction models, and guide personalized treatment path selection. The government should provide policy support, financial assistance and supervision for the treatment of neck pain. Clinicians should recommend exercise therapy and cognitive behavioral intervention, achieve long-term follow-up management through telemedicine technology, and participate in international diagnosis and treatment consensus to promote the synchronization of clinical practice and cutting-edge evidence. In particular, the disease burden of neck pain in the high-middle SDI region is the heaviest, which should be paid more attention to. According to the characteristics of occupational characteristics and the distribution of medical resources in this region, enterprises should configure ergonomic workstations to prevent and treat occupational neck pain in key industries, which can effectively reduce social medical costs and improve the life of patients. It also provides a paradigm reference for the prevention and control of other chronic musculoskeletal diseases.

This study acknowledges certain limitations. Firstly, insufficient medical infrastructure in underdeveloped regions limits accurate diagnosis and screening of neck pain. The scarcity of raw data may underestimate the actual burden of neck pain, potentially compromising the precision of the effect of age, period and cohort estimation and misleading risk factor identification for intervention evaluation. Future studies should enhance medical infrastructure in underdeveloped areas using advanced technology to improve diagnostic accuracy and early screening rates for neck pain. Variations in diagnostic criteria, willingness to seek medical care, and medical record completeness may hinder accurate cross-regional comparisons. It is recommended that future cross-country studies establish uniform diagnostic standards and implement community-based screenings by trained volunteers in areas with limited diagnostic capabilities to enhance comparability between regions. Lastly, the absence of detailed pain rating data in the GBD database prevents in-depth analysis of the pain burden. Future research should empirically investigate the burden of neck pain among younger populations using questionnaires specifically designed for assessing neck pain intensity.

Conclusion

This study examined the neck pain burden in young people globally, regionally, and nationally from 1990 to 2021. The global trends in prevalence, incidence and DALYs of neck pain were relatively stable. However, different and even opposite trends were observed between different areas and countries, illustrating the existence of strong regional heterogeneity. Subgroup analyses indicated that the burden of neck pain increased with age and that neck pain was much more severe in women than in men. In addition, the negative correlation between neck pain incidence and SDI levels was revealed. The effects of age, period and cohort for neck pain burden were also investigated. Predictive modeling showed by 2050, the number of young people suffering from neck pain will continue to grow, posing a global public health challenge in the future and the need to target prevention and control in key populations and areas.

Supplemental Material

Supplemental Material - Global, Regional, and National Burden of Neck Pain in Young Population, 1990–2021: An Age–Period–Cohort Analysis and Projections to 2050 Based on the Global Burden of Disease Study 2021

Supplemental Material for Global, Regional, and National Burden of Neck Pain in Young Population, 1990–2021: An Age–Period–Cohort Analysis and Projections to 2050 Based on the Global Burden of Disease Study 2021 by Xiaohan Jing, Yuan Wang, Yuchen Zhang, Fan Li, Di Tian, Feilong Zhang, Yuting Chen, and Ye Wu in Political Research Quarterly

Footnotes

Acknowledgments

We acknowledge GBD 2021 collaborators whose outstanding contributions have enabled us to complete this study.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by grants from the Open Fund Project of Anhui Provincial Laboratory for Inflammatory Immune Diseases (IMMDL202405).

ORCID iD

Ye Wu

Data Availability Statement

The datasets generated and/or analysed during the current study are available in the GBD 2021 repository, available from .

Supplemental Material

Supplemental material for this article is available online.

Appendix

References

Kazeminasab

Nejadghaderi

Amiri

, et al. Neck pain: global epidemiology, trends and risk factors. BMC Musculoskelet Disord. 2022;23:26.

Cohen

. Epidemiology, diagnosis, and treatment of neck pain. Mayo Clin Proc. 2015;90:284-299.

Hoy

Protani

Buchbinder

. The epidemiology of neck pain. Best Pract Res Clin Rheumatol. 2010;24:783-792.

Roijezon

Bjorklund

Bergenheim

Djupsjöbacka

. A novel method for neck coordination exercise--a pilot study on persons with chronic non-specific neck pain. J NeuroEng Rehabil. 2008;5:36.

Cohen

Hooten

. Advances in the diagnosis and management of neck pain. BMJ Br Med J (Clin Res Ed). 2017;358:j3221.

Hernández-Secorún

Abenia-Benedí

Borrella-Andrés

, et al. Effectiveness of dry needling in improving pain and function in comparison with other techniques in patients with chronic neck pain: a systematic review and meta-analysis. Pain Res Manag. 2023;2023:1-14.

Vassilaki

Hurwitz

. Insights in public health: perspectives on pain in the low back and neck: global burden, epidemiology, and management. Hawaii J Med Public Health. 2014;73:122-126.

Jahre

Grotle

Smedbråten

, et al. Risk factors for non-specific neck pain in young adults. A systematic review. BMC Muscoskelet Disord. 2020;21:366.

Jun

Zoe

Johnston

O'Leary

. Physical risk factors for developing non-specific neck pain in office workers: a systematic review and meta-analysis. Int Arch Occup Environ Health. 2017;90:373-410.

10.

Rosenberg

Check

Anderson

. A web tool for age-period-cohort analysis of cancer incidence and mortality rates. Cancer Epidemiol Biomarkers Prev. 2014;23:2296-2302.

11.

Yang

Schulhofer-Wohl

, et al. The intrinsic estimator for age-period-cohort analysis: what it is and how to use it. Am J Sociol. 2008;113(6):1697-1736.

12.

Chen

Wang

Zhao

Zhang

Kan

. Application of the arima model in forecasting the incidence of tuberculosis in Anhui during covid-19 pandemic from 2021 to 2022. Infect Drug Resist. 2022;15:3503-3512.

13.

Chen

O Leary

Johnston

. Modifiable individual and work-related factors associated with neck pain in 740 office workers: a cross-sectional study. Braz J Phys Ther. 2018;22:318-327.

14.

Global, regional, and national burden of neck pain, 1990-2020, and projections to 2050: a systematic analysis of the global burden of disease study 2021. Lancet Rheumatol. 2024;6:e142-e155.

15.

Xia

Liu

, et al. Burden of neck pain in general population of China, 1990–2019: an analysis for the global burden of disease study 2019. J Glob Health. 2024;14:04066.

16.

Sterud

Tynes

. Work-related psychosocial and mechanical risk factors for low back pain: a 3-year follow-up study of the general working population in Norway. Occup Environ Med. 2013;70:296-302.

17.

Carvalho

DPD

Rocha

Pinho

ECD

Tomaschewski-Barlem

Barlem

ELD

Goulart

. Workloads and burnout of nursing workers. Rev Bras Enferm. 2019;72:1435-1441.

18.

Al-Hadidi

Bsisu

AlRyalat

, et al. Association between mobile phone use and neck pain in university students: a cross-sectional study using numeric rating scale for evaluation of neck pain. PLoS One. 2019;14:e217231.

19.

Coury

HJCG

Alfredo Léo

Kumar

. Effects of progressive levels of industrial automation on force and repetitive movements of the wrist. Int J Ind Ergon. 2000;25:587-595.

20.

Charnes

ACWRE

. Measuring the efficiency of decision making units. Eur J Oper Res. 1978;2:429.

21.

Cassou

Derriennic

Monfort

Norton

Touranchet

. Chronic neck and shoulder pain, age, and working conditions: longitudinal results from a large random sample in France. Occup Environ Med. 2002;59:537-544.

22.

Cote

van der Velde

Cassidy

, et al. The burden and determinants of neck pain in workers: results of the bone and joint decade 2000-2010 task force on neck pain and its associated disorders. Spine. 2008;33:S60-S74.

23.

Dianat

Karimi

. Musculoskeletal symptoms among handicraft workers engaged in hand sewing tasks. J Occup Health. 2016;58:644-652.

24.

Oliv

Noor

Gustafsson

Hagberg

. A lower level of physically demanding work is associated with excellent work ability in men and women with neck pain in different age groups. Saf Health Work. 2017;8:356-363.

25.

Czępińska

Zawadka

Wójcik-Załuska

Rzezak- Siwiec

Gawda

. Association between pain intensity, neck disability index, and working conditions among women employed in horticulture. Ann Agric Environ Med. 2023;30:531-535.

26.

Bonilla-Barba

Florencio

Rodríguez-Jiménez

Falla

Fernández-de-las-Peñas

Ortega-Santiago

. Women with mechanical neck pain exhibit increased activation of their superficial neck extensors when performing the cranio-cervical flexion test. Musculoskelet Sci Pract. 2020;49:102222.

27.

Johnston

Souvlis

Jimmieson

Jull

. Associations between individual and workplace risk factors for self-reported neck pain and disability among female office workers. Appl Ergon. 2008;39:171-182.

28.

Briggs

Straker

Burnett

Wark

. Chronic low back pain is associated with reduced vertebral bone mineral measures in community-dwelling adults. BMC Musculoskelet Disord. 2012;13:49.

29.

Johnston

Jimmieson

Jull

Souvlis

. Contribution of individual, workplace, psychosocial and physiological factors to neck pain in female office workers. Eur J Pain. 2009;13:985-991.

30.

Mendes-Fernandes

Puente-González

Márquez-Vera

Vila-Chã

Méndez-Sánchez

. Effects of global postural reeducation versus specific therapeutic neck exercises on pain, disability, postural control, and neuromuscular efficiency in women with chronic nonspecific neck pain: study protocol for a randomized, parallel, clinical trial. Int J Environ Res Public Health. 2021;18:10704.

31.

Genç ve orta yaş erkeklerde kronik bel ağrısı ve kemik mineral yoğunluğu arasındaki İlişki. Türkiye Fiziksel Tıp Ve Rehabilitasyon Dergisi. 2012;58:294-298.

32.

Paksaichol

Janwantanakul

Purepong

Pensri

van der Beek

. Office workers' risk factors for the development of non-specific neck pain: a systematic review of prospective cohort studies. Occup Environ Med. 2012;69:610-618.

33.

Nejadghaderi

Mousavi

Sullman

MJM

Kolahi

Namazi Shabestari

Safiri

. The burden of neck pain among adults aged 70 years and older in Iran, 1990–2019. Health Sci Rep. 2023;6:e1477.

34.

Ahangar-Sirous

Alizadeh

Nejadghaderi

, et al. The burden of neck pain in the middle East and North Africa region, 1990–2019. Heliyon. 2023;9:e21296.

35.

Ayhualem

Alamer

Dabi

Bogale

Abebe

Chala

. Burden of neck pain and associated factors among smart phone user students in University of Gondar, Ethiopia. PLoS One. 2021;16:e256794.

36.

Muntner

Wildman

, et al. Prevalence of physical activity among Chinese adults: results from the international collaborative study of cardiovascular disease in Asia. Am J Public Health (1971). 2005;95:1631-1636.

37.

World

Burton

. Who Healthy Workplace Framework and Model: Background and Supporting Literature and Practices. Geneva: World Health Organization; 2010.

38.

Punnett

Wegman

. Work-related musculoskeletal disorders: the epidemiologic evidence and the debate. J Electromyogr Kinesiol. 2004;14:13-23.

39.

Xie

Szeto

GPY

Dai

Madeleine

. A comparison of muscle activity in using touchscreen smartphone among young people with and without chronic neck–shoulder pain. Ergonomics. 2016;59:61-72.

40.

Briggs

Jordan

Sharma

, et al. Context and priorities for health systems strengthening for pain and disability in low- and middle-income countries: a secondary qualitative study and content analysis of health policies. Health Policy Plan. 2023;38:129-149.

41.

Jing

Wei

. Risk factors of non-specific neck pain and low back pain in computer-using office workers in China: a cross-sectional study. BMJ Open. 2017;7:e14914.

42.

Mesa-Castrillon

Beckenkamp

Ferreira

, et al. Global prevalence of musculoskeletal pain in rural and urban populations. A systematic review with meta-analysis. Musculoskeletal pain in rural and urban populations. Aust J Rural Health. 2024;32:864-876.

43.

Benach

Vives

Amable

Vanroelen

Tarafa

Muntaner

. Precarious employment: understanding an emerging social determinant of health. Annu Rev Public Health. 2014;35:229-253.

44.

McIntyre

Garshong

Mtei

, et al. Beyond fragmentation and towards universal coverage: insights from Ghana, South Africa and the United Republic of Tanzania. Bull World Health Organ. 2008;86:871-876.

45.

Kumar

KVR

Elias

. Real-time tracking of human neck postures and movements. Healthcare. 2021;9:1755.

46.

Gong

Qiu

Jiang

, et al. Maltol ameliorates intervertebral disc degeneration through inhibiting PI3K/AKT/NF-kappab pathway and regulating NLRP3 inflammasome-mediated pyroptosis. Inflammopharmacology. 2023;31:369-384.

47.

Tian

Zhou

, et al. Selenium nanoparticles ameliorate lumbar disc degeneration by restoring GPX1-mediated redox homeostasis and mitochondrial function of nucleus pulposus cells. J Nanobiotechnology. 2024;22:634.

48.

Zhang

Grant

Shivakumar

, et al. Genome-wide association analysis across 16,956 patients identifies a novel genetic association between BMP6, NIPAL1, CNGA1 and spondylosis. Spine. 2021;46:E625-E631.

49.

Zeng

, et al. Transcriptome-wide association study identifies new susceptibility genes for degenerative cervical spondylosis. Bone Joint Res. 2023;12:80-90.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.90 MB