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Joinpoint regression (JR) is implemented in time series analysis to identify trend changes without predefined shift points. This study compares the performance of the Joinpoint Regression Program (JRP) and R “segmented” package in detecting joinpoints using simulated and real-world data on pediatric mental health (MH)–related hospitalizations. Simulated datasets (n = 1000) were generated with varying residual autocorrelation, trend change magnitude, and joinpoint locations to evaluate the performance of both software (accuracy, specificity, coverage of the 95% confidence interval [95% CI] coverage, monthly percent change [MPC], coverage of the last segment). In addition, monthly proportions of pediatric MH-related hospitalizations (January 2016–December 2023) were analyzed to compare the number of joinpoints identified and the average monthly percent change (AMPC). In simulations without residual autocorrelation and no joinpoint, JRP exhibited a specificity of 92.7% compared to 97.9% for R. With an important trend change, the accuracy and 95% CI coverage were 59.0% and 81.7% using JRP and 69.4% and 76.8% using R. The coverage of the MPC of the last time segment varied from 93.0% to 97.9% using JRP and from 0% to 98.3% using R. When residual autocorrelation was introduced with a moderate trend change toward the end of the dataset, the accuracy and 95% CI coverage were 72.6% and 95.0% using JRP and 52.8% and 67.1% using R. The coverage of the MPC of the last time segment varied from 4.8% to 98.6% using JRP and from 0% to 96.9% with R. In the analysis of MH-related hospitalizations, among girls aged 6–11 years, JRP detected four joinpoints (AMPC: 0.11%), while R found 1 (AMPC: 0.05%). For boys aged 12–17 years, JRP identified four joinpoints vs three using R. The choice of JR software should be guided by the characteristics of the dataset. The R “segmented” package may be more appropriate for datasets without residual autocorrelation, whereas JRP appears to provide more reliable estimates when analyzing autocorrelated health care data or data with no underlying trend changes. This study compares two methods for analyzing changes in trends over time. The two tools examined are the Joinpoint Regression Program (JRP) and the R “segmented” package. Using both simulated data and real-world hospital data, we assessed the performance of these tools. The simulated data included two scenarios: one without residual autocorrelation (simpler) and another with residual autocorrelation (where data points are related to previous ones, often seen in health care data). In the simpler scenario, the R package outperformed JRP by being more accurate in detecting changes and avoiding false detections. It also provided more precise estimates, with smaller uncertainty around the change points. However, when dealing with the more complex scenario involving residual autocorrelation, the JRP performed better, especially when changes occurred later in the timeline. However, early trend changes in the time series were challenging to detect for both JRP and R software. When analyzing real-world data on children's mental health hospitalizations, the JRP tended to identify more changes in trends than the R package. However, both softwares produced broadly similar results for the overall trends. The JRP is user-friendly and works well with data that include complex patterns like residual autocorrelation, but it does not account for seasonal effects and may detect more changes than are truly present. The R package, on the other hand, offers greater precision and flexibility for simpler data but requires more advanced programming skills and does not perform as well when handling data with residual autocorrelation. In summary, the choice between these tools should be driven by the type of data being analyzed: the R package is better for straightforward data, while the JRP is more suited for complex datasets such as those found in health care. •In simulations, JRP had better performance metrics in the presence of residual autocorrelation.•In real-world data, JRP consistently identified more joinpoints in the time series.•We provide evidence on the performance of joinpoint analysis in JRP and R software.•The choice of the software should be guided by the characteristics of the time series.•For health-care time series data, joinpoint analysis using JRP is recommended.

PurposeUnderstanding secular trends of thyroid cancer is critical to plan strategies for cancer prevention and control. Our aim was to estimate the incidence and mortality trends of thyroid cancer in China during 2005–2015.MethodsA retrospective cohort evaluation of thyroid cancer cases and deaths during 2005–2015 was performed using population-based data from the Chinese Cancer Registry Annual Report. The incidence and mortality rates of thyroid cancer were stratified by gender, age group (0, 1–4, 5–9, 10–14…80–84, 85–), and area (urban or rural). A Joinpoint regression model was used to examine secular trends.ResultsIn China, the age-standardized incidence was 3.21/105 in 2005, and increased to 9.61/105 in 2015. Besides, a significant increase incidence rate was observed with the average annual percent change (AAPC) of 12.4% (95% CI: 10.5%–14.4%) in the period 2005–2015. The age-standardized mortality was 0.30/105 in 2005 and 0.35/105 in 2015, and the AAPC was 2.9% (95% CI: 1.3%–4.5%). For both incidence and mortality, the rates of thyroid cancer were much higher in females than in males, and in urban areas rather than rural areas; however, the rates of increasing trends showed no significant differences. With respect to the highest age-specific rates, it appeared in the age group of 50–54 years old for incidence and in the age group of 80–84 years old for mortality. Notably, the rate of increasing incidence trend was lower in older age groups, especially for people aged 70–79 years old.ConclusionA rapid increase in incidence and a moderate increase in mortality of thyroid cancer were observed from 2005 to 2015 in our study. Effective measures and tailored programs should be taken to curb the growth trend and reduce the disease burden.

Gastric cancer (GC) represents a major global health issue. Understanding its current burden and divergent regional trends is critical for formulating effective prevention strategies. We report on the incidence, mortality, and disability-adjusted life-years (DALYs) due to gastric cancer in 204 countries and territories from 21 regions between 1990 and 2021 and provide projections of future trends. Using Global Burden of Disease 2021 data, we evaluated GC age-standardized incidence rates (ASIR), age-standardized death rates (ASDR), DALYs, and age-standardized DALY rates (ASDR) across 204 countries and territories from 1990 to 2021. Metrics were stratified by region, country, sociodemographic index (SDI), age, and sex. Trends were evaluated through joinpoint regression, and Bayesian age-period-cohort (BAPC) model was used to project incidence, mortality, and DALYs to 2045. In 2021, the global count estimated of GC-related deaths was 954,373.60, while the incidence exceeded 1.23 million cases. Notably, China alone accounted for 611,799 GC cases and 445,013 GC-related deaths in 2021. Global ASIR, ASDR, and ASR of GC declined annually by 1.77%, 2.18%, and 2.44%, respectively from 1990 to 2021. Males exhibit a higher ASIR, ASDR, and ASR. Andean Latin America and East Asia carry the heaviest burden of GC. The population aged 70-74 years has the highest number of incident cases and deaths. Higher-SDI regions demonstrated more rapid declines in mortality, incidence, and ASR than lower-SDI regions. Smoking and high-sodium diet were the primary risk factors for GC burden. Projections for 2045 suggest a continued decrease in GC burden. Since 1990, the global ASDR, ASIR, and ASR for GC have consistently declined. However, substantial disparities persist across regions, countries, age groups, and sexes. Tailored prevention and intervention strategies, informed by regional characteristics and risk factors, are essential to effectively reduce the global GC burden.

BACKGROUND:Recent research on the US opioid epidemic has focused on the white or total population and has largely been limited to data after 1999. However, understanding racial differences in long-term trends by opioid type may contribute to improving interventions. METHODS:Using multiple cause of death data, we calculated age-standardized opioid mortality rates, by race and opioid type, for the US resident population from 1979 to 2015. We analyzed trends in mortality rates using joinpoint regression. RESULTS:From 1979 to 2015, the long-term trends in opioid-related mortality for non-Hispanic blacks and non-Hispanic whites went through three successive waves. In the first wave, from 1979 to the mid-1990s, the epidemic affected both populations and was driven by heroin. In the second wave, from the mid-1990s to 2010, the increase in opioid mortality was driven by natural/semi-synthetic opioids (i.e., codeine, morphine, hydrocodone, or oxycodone) among whites, while there was no increase in mortality for blacks. In the current wave, increases in opioid mortality for both populations have been driven by heroin and synthetic opioids (i.e., fentanyl and its analogues). Heroin rates are currently increasing at 31% (95% CI27, 35) per year for whites and 34% (95% CI30, 40) for blacks. Concurrently, respective synthetic opioids are increasing at 79% (95% CI50, 112) and 107% (95% CI-15, 404) annually. CONCLUSION:Since 1979, the nature of the opioid epidemic has shifted from heroin to prescription opioids for the white population to increasing of heroin/synthetic deaths for both black and white populations.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

Osteoarthritis (OA) is a major global health burden, affecting millions and causing significant disability. Understanding its trends and determinants is crucial for effective management and prevention. We analyzed data from the Global Burden of Diseases (GBD) study 2021 to assess OA incidence, Years Lived with Disability (YLDs), and age-standardized rates (ASIR/ASYR) from 1990 to 2021. We explored trends and determinants across gender, region, and Socio-Demographic Index (SDI) quintiles using Joinpoint regression, Age-Period-Cohort (APC) modeling, decomposition, and inequality analyses. The global incidence of OA surged from 20.9 million in 1990 to 46.6 million cases in 2021, with an AAPC of 0.29%. Correspondingly, YLDs escalated from 8.92 million to 21.30 million, reflecting an AAPC of 0.30%. Disparities exist across SDI quintiles, with higher rates observed in high SDI countries. Women consistently experience a higher burden compared to men. Asian regions demonstrate the fastest rise in ASYR. High BMI contributes significantly to OA burden, particularly in high SDI countries. The rising burden of OA necessitates urgent attention. Interventions targeting modifiable risk factors, such as obesity, and early detection and management strategies are crucial. Addressing gender disparities and health inequalities, particularly in high SDI countries, is essential for effective OA prevention and control.

Background: The aim of this study was to analyze the trends of multiple births at both national and provincial levels in Iran from 2014 to 2023. Methods: Data on the number of live births and multiple births from 2014 to 2023 at national and provincial levels were obtained from the Iran’s Bureau of Vital Statistics. The multiple birth rate (MBR), defined as the number of live births from multiple births per 1,000 live births, was calculated annually. To examine temporal trends and detect significant changes in MBR over the study period, joinpoint regression analysis was performed. Annual percent change (APC) and average annual percent change (AAPC) were calculated for the entire period. Result: The national AAPC in the MBR was estimated at 2.38% (95%CI: 1.95 to 2.76) over the entire study period. A significant shift in trend was identified in 2020. Specifically, the APC from 2014 to 2020 was 0.24%. However, from 2020 to 2023, the APC markedly increased to 6.8%, reflecting a substantial rise in MBR during this latter period. Furthermore, the study findings demonstrated that nearly all provinces across the country have exhibited an upward trend in MBR in recent years. Conclusion: The increasing trend of multiple births in Iran aligns with global patterns. Several factors may have contributed to this rise, including increased maternal age at childbirth, higher prevalence of infertility, expanded use of assisted reproductive technologies (ARTs), and shifts in population policies.  

Background Rotavirus is the leading global pathogen of diarrhea-associated mortality and poses a great threat to public health in all age groups. This study aimed to explore the global burden and 30-year change patterns of rotavirus infection-associated deaths. Methods Based on the Global Burden of Disease 2019 Study (GBD 2019), we analyzed the age-standardized death rate (ASDR) of rotavirus infection by sex, geographical region, and sociodemographic index (SDI) from 1990 to 2019. A Joinpoint regression model was used to analyze the global trends in rotavirus infection over the 30 years, SaTScan software was used to detect the spatial and temporal aggregations, and a generalized linear model to explore the relationship between sociodemographic factors and death rates of rotavirus infection. Results Globally, rotavirus infection was the leading cause of diarrheal deaths, accounting for 19.11% of deaths from diarrhea in 2019. Rotavirus caused a higher death burden in African, Oceanian, and South Asian countries in the past three decades. The ASDR of rotavirus declined from 11.39 (95% uncertainty interval [95% UI] 5.46–19.48) per 100,000 people in 1990 to 3.41 (95% UI 1.60–6.01) per 100,000 people in 2019, with an average annual percentage change (AAPC) (− 4.07%, P  < 0.05). However, a significant uptrend was found in high-income North America (AAPC = 1.79%, P  < 0.05). The death rate was the highest among children under 5 years worldwide. However, the death rates of elderly individuals over 70 years were higher than those of children under 5 years in 2019 among high, high-middle, middle, and low-middle SDI regions. Current health expenditure, gross domestic product per capita, and the number of physicians per 1000 people were significantly negatively correlated with death rates of rotavirus. Conclusions Although the global trends in the rotavirus burden have decreased substantially over the past three decades, the burden of rotavirus remained high in Africa, Oceania, and South Asia. Children under 5 years and elderly individuals over 70 years were the populations most at risk for rotavirus infection-associated deaths, especially elderly individuals over 70 years in relatively high SDI regions. More attention should be paid to these areas and populations, and effective public health policies should be implemented in the future.

Background Worldwide, cervical cancer is the second-most-common malignancy of the female reproductive system. Due to its large population, China accounted for 11.9% of cervical cancer deaths, and 12.3% of global cervical cancer DALYs in 2017. In 2009, China launched a nationwide screening program, yet mortality from cervical cancer has shown an upward trend in recent years. The aim of this study was to explore factors affecting cervical cancer mortality rates in China, and contribute to their future reduction. Methods In this descriptive study, a Joinpoint regression analysis and age-period-cohort (APC) model based on the intrinsic estimator (IE) algorithm were utilized. Data from the period 1989–2018 were extracted from the International Agency for Research on Cancer (IARC) Database of WHO (1989–2000) and China Health Statistical Yearbook database (2002–2018). Results Our study found mortality from cervical cancer to have initially declined, but increase thereafter over the entire observation period in both rural and urban China. The influence of age, period and cohort effect on the mortality rate had statistical significance. The effect of age increased with years, becoming a contributing factor in women aged over 45 years countrywide. Conversely, the cohort effect became a protective factor for women born after 1938 in urban areas, and for women born after 1958 in rural areas. The period effect was relatively less impactful. Conclusions The study indicates that organized cervical screening projects facilitated the identification of potential patients, or patients with comorbidities. Correspondingly, mortality was found to increase with incidence, particularly among elderly women, indicating that newly diagnosed patients were at an advanced stage of cervical cancer, or were not receiving appropriate treatment. Therefore, the coverage of cervical cancer screening should be improved, and women’s health awareness promoted. Early diagnosis and treatment is critical to reduce the disease burden and improve outcomes.

Metabolic dysfunction-associated fatty liver disease (MAFLD) is the most prevalent chronic liver disease globally, driven by rising obesity, metabolic syndrome (MetS), and type 2 diabetes mellitus (T2DM). This study evaluates the global, regional, and national burden of MAFLD-related diseases from 1990 to 2021 and projects future trends. Data were sourced from the Global Burden of Disease (GBD) 2021 database, including estimates for the incidence, prevalence, mortality, and disability-adjusted life years (DALYs) associated with MAFLD, MAFLD-related cirrhosis, and MASH-related liver cancer. Countries were classified into 21 regions and five socio-demographic index (SDI) quintiles to analyze health disparities. Decomposition analyses assessed the contributions of population growth, aging, and epidemiological shifts. Future trends were modeled using the Bayesian Age-Period-Cohort (BAPC) framework. In 2021, approximately 1.27 billion MAFLD cases were reported globally, with an age-standardized prevalence rate (ASPR) of 15,018 per 100,000. The highest incidence occurred in South and East Asia. Mortality reached 138,328 cases for MAFLD and 97,403 for MAFLD-related cirrhosis. Decomposition analyses highlighted population growth and aging as key drivers. BAPC projections indicate a continued rise in MAFLD burden, particularly in low- and middle-income countries. This study underscores the increasing global burden of MAFLD and its complications. Targeted public health interventions focusing on prevention and early management are urgently needed to mitigate future impacts.

Background Cervical cancer is the fourth most common cancer that occurs to women worldwide. This study aims to assess trends in incidence and mortality of cervical cancer in India and its states over past three decades for tracking the progress of strategies for the prevention and control of cervical cancer. Methods Data on cervical cancer incidence and mortality from 1990 to 2019 for India and its states were extracted from Global Burden of Disease study and were utilized for the analysis. Spatial and rank map has been used to see the changes in incidence and mortality of cervical cancer in different Indian states. Further, joinpoint regression analysis is applied to determine the magnitude of the time trends in the age standardized incidence and mortality rates of cervical cancer. We obtained the average annual percent change (AAPC) and corresponding 95% confidence intervals (CI) for each state. Results Overall, from 1990 to 2019 Jharkhand (Incidence: -50.22%; Mortality: -56.16%) recorded the highest percentage decrement in cervical cancer incidence and mortality followed by the Himachal Pradesh (Incidence: -48.34%; Mortality: -53.37%). Tamilnadu (1 st rank), Jammu & Kashmir and Ladakh (32 nd rank) maintained the same rank over the period of three decade for age standardized cervical cancer incidence and mortality. The regression model showed a significant declining trend in India between 1990 and 2019 for age standardized incidence rate (AAPC: −0.82; 95%CI: −1.39 to −0.25; p < 0.05) with highest decline in the period 1998-2005 (AAPC: −3.22; 95%CI: −3.83 to −2.59; p < 0.05). Similarly, a significant declining trend was observed in the age standardized mortality rate of India between 1990 and 2019(AAPC: −1.35; 95%CI: −1.96 to −0.75; p < 0.05) with highest decline in the period 1998-2005 (AAPC: −3.52; 95%CI: −4.17 to −2.86; p < 0.05). Conclusion Though the incidence and mortality of cervical cancer declined over past three decades but it is still a major public health problem in India. Information, education and communication activities for girls, boys, parents and community for the prevention and control of cervical cancer should be provided throughout the country.