Rib and Sternum Fractures From Falls: Global Burden of Disease and Predictions

Abstract

Background: By combining existing Global Burden of Disease (GBD) data with the economic conditions of different regions, we can better understand disease trends and make more accurate estimations, facilitating effective public health interventions. Medical institutions can consequently allocate resources more efficiently. For patients, this helps lower disease risk and reduce the overall disease burden in affected areas.

Methods: We analyzed health patterns in 204 countries using GBD 2021 methodologies and conducted separate analyses of disease burden in China and worldwide. We estimated incidence, prevalence, and years lived with disability (YLDs). We further assessed disease status by incorporating Socio-Demographic Index (SDI) values. In addition, we used Mendelian randomization to identify factors leading from falls to thoracic rib fractures, and we investigated the key protein involved in thoracic rib fractures through detection of 4907 plasma proteins.

Results: From 1990 to 2021, the age-standardized incidence rate (ASIR) and age-standardized prevalence rate (ASPR) generally showed an upward trend, although male ASIR, and ASPR displayed a slight decline. In China, however, ASIR and ASPR reached a turning point in 2000, dipped in 2005, then trended upward again. Morbidity and prevalence were negatively correlated with SDI. Based on Mendelian randomization analyses, falls leading to thoracic rib fractures were linked to education level and osteoporosis. Moreover, HAMP was identified as the key protein in thoracic rib fractures.

Conclusion: As global populations age, analyzing the global burden of thoracic rib fractures caused by falls from 1990 to 2021 can help guide the development of effective public health prevention strategies and optimize the allocation of existing medical resources.

Keywords: ASIR; ASPR; GBD; MR; fall.

Figure 1.

Trends of ASIR and ASPR in both sexes. (A) In China, ASIR for both sexes rose before 2000, declined before 2005, and rebounded thereafter. (B) Similarly, ASPR in China increased before 2000, dipped before 2005, then resurged after 2005. (C) Globally, the incidence among both sexes is increasing, yet ASIR continues to decline. (D) Worldwide prevalence is on the rise, whereas ASPR remains on a downward trajectory. (E) In China, incidence among individuals aged over 70 has grown in both sexes. (F) Likewise, prevalence among those over 70 has increased in both sexes in China. (G) Globally, incidence among individuals over 70 has also risen. (H) Worldwide, prevalence among those over 70 has similarly increased.

Figure 2.

Differences in disease burden by age group. (A) In 1990 China, the highest incidence was observed among individuals aged 20 to 24. (B) In 1990 China, prevalence peaked in men aged 35 to 39 and in women aged 65 to 69. (C) In 1990 worldwide, men experienced their highest incidence at ages 20 to 24, while women peaked at 75 to 79. (D) In 1990 worldwide, men’s prevalence was highest at ages 55 to 59, while women peaked at 75 to 79. (E) In 2021 China, the largest incidence for men occurred at 30 to 34, while it was 80 to 84 for women. (F) In 2021 China, men’s prevalence was highest at 55 to 59, whereas women’s incidence peaked at 65 to 69. (G) In 2021 globally, men showed the largest incidence at ages 30 to 34, whereas women’s incidence peaked at 80 to 84. (H) In 2021 globally, men’s prevalence was highest at 65 to 69, and women’s incidence was highest at 80 to 84.

Figure 3.

Joinpoint analysis of ASIR and ASPR (1990-2021) in China and globally. (A) For Chinese women, the ASIR progressed through 4 intervals: 1990 to 2001 (APC = +0.75, P < .05), 2001 to 2005 (APC = −8.35, P < .05), 2005 to 2010 (APC = +1.27), and 2010 to 2021 (APC = +5.41, P < .05). (B) Among Chinese men, the ASIR showed 4 intervals: 1990 to 2001 (APC = +0.49, P < .05), 2001 to 2005 (APC = −7.18, P < .05), 2005 to 2010 (APC = +1.07), and 2010 to 2021 (APC = +5.24, P < .05). (C) For women globally, the ASIR was subdivided into 6 intervals: 1990 to 1994 (APC = −0.44, P < .05), 1994 to 2000 (APC = −0.08), 2000 to 2005 (APC = −0.79, P < .05), 2005 to 2010 (APC = −0.01), 2010 to 2018 (APC = −0.82, P < .05), and 2018 to 2021 (APC = −0.23, P < .05). (D) Among men worldwide, the ASIR showed 6 distinct segments: 1990 to 2000 (APC = −0.35, P < .05), 2000 to 2005 (APC = −1.08, P < .05), 2005 to 2010 (APC = −0.58, P < .05), 2010 to 2014 (APC = −1.24, P < .05), 2014 to 2018 (APC = −0.83, P < .05), and 2018 to 2021 (APC = −0.03). (E) For Chinese women, the ASPR was split into 4 intervals: 1990 to 2001 (APC = +0.47, P < .05), 2001 to 2005 (APC = −8.90, P < .05), 2005 to 2010 (APC =+0.82), and 2010 to 2021 (APC = +5.21, P < .05). (F) For Chinese men, the ASIR progressed through 4 intervals: 1990 to 2001 (APC = +0.29, P < .05), 2001 to 2005 (APC = −7.73, P < .05), 2005 to 2010 (APC = +0.49), and 2010 to 2021 (APC = +5.13, P < .05). (G) Among women globally, the ASPR included 6 phases: 1990 to 1993 (APC = −0.42, P < .05), 1993 to 2000 (APC = −0.20, P < .05), 2000 to 2005 (APC = −0.83, P < .05), 2005 to 2010 (APC = −0.13, P < .05), 2010 to 2017 (APC = −1.10, P < .05), and 2017 to 2021 (APC = −0.38, P < .05). (H) Finally, for men worldwide, the ASPR was subdivided into 6 periods: 1990 to 2000 (APC = −0.44, P < .05), 2000 to 2005 (APC = −1.18, P < .05), 2005 to 2010 (APC = −0.76, P < .05), 2010 to 2014 (APC = −1.53, P < .05), 2014 to 2018 (APC = −0.97, P < .05), and 2018 to 2021 (APC = −0.00).

Figure 4.

APC (Age-Period-Cohort) analysis the age effect is illustrated by both the longitudinal and cross-sectional age curves. Age deviations integrate these 2 curves (represented as Long vs Cross RR) and capture any non-linear effects, akin to observing linear age trends. The period effect is shown via Fitted Temporal Trends, Period RR, and Period deviations. Fitted Temporal Trends depict incidence or mortality for a reference cohort after deviations are corrected—similar to age-standardized rates. Period deviations combine these Fitted Temporal Trends with any non-linear influences identified by Period RR, approximating linear trends across different time periods. Finally, the birth cohort effect is represented by Cohort RR and Local Drifts, with cohort deviations integrating non-linear aspects of Cohort RR and local drift, again resembling linear trends. (A) Among the same birth cohort in China, mortality gradually increases with age. Based on the Period RR, mortality has risen more slowly in recent years. (B) Globally, mortality also increases with age within the same birth cohort. However, the Period RR indicates a decline overall. Specifically, mortality rises for individuals born before 1930, then gradually decreases for those born after 1930.

Figure 5.

Age-specific APC analysis. This figure presents age-specific incidence data across varying time periods, birth cohorts, and age groups. Each row covers a 10-year span of age-specific incidence. (A) Thoracic rib fracture incidence from falls in China. (B) Thoracic rib fracture incidence from falls globally.

Figure 6.

Decomposition of disease drivers. (A) In China, epidemiological changes are the largest contributor to ASIR. (B) Epidemiological changes also dominate ASPR in China. (C) Aging plays the most significant role in China’s YLDs. (D) Globally, population shifts emerge as the primary driver of ASIR. (E) For global ASPR, epidemiological changes account for the largest share. (F) Similarly, epidemiological changes remain the major factor influencing global YLDs.

Figure 7.

Projected Disease Trends Over the Next 15 years (A) ASIR among men in China. (B) ASIR among women in China. (C) ASIR among men globally. (D) ASIR among women globally. (E) ASPR among men in China. (F) ASPR among women in China. (G) ASPR among men globally. (H) ASPR among men globally.

Figure 8.

Disease burden by region. (A) ASIR across 22 regions. (B) ASPR across 22 regions. (C) ASIR across 204 countries. (D) ASPR across 204 countries. (E and F) Frontier analysis.

Figure 9.

MR Analysis (A) A causal relationship between education and fall-induced sternorib fractures. (B) A causal relationship between osteoporosis and fall-induced thoracic rib fractures. (C) Screening of 4907 plasma proteins highlights key proteins involved in fall-related rib fractures. (D) GO enrichment analysis of key proteins. (E) KEGG enrichment analysis of key proteins.