Linear Trend Change Research Articles

Trends in diabetic ketoacidosis in Victoria, Australia 2002–2016

BackgroundInternational longitudinal studies have indicated an increasing incidence of diabetic ketoacidosis (DKA). We aim to examine the incident trends, demographic differences, length of stay and mortality for DKA in adults with type 1 diabetes (T1D) and type 2 diabetes (T2D) in Victoria, Australia from 2002 to 2016.MethodsAge and sex adjusted incident trends, length of stay and mortality for DKA was retrospectively obtained using the Victorian Admitted Episode Dataset between 2002 and 2016. Data for adults with T1D and T2D was obtained from the National Diabetes Services Scheme (NDSS). Joinpoint regression analysis was used to identify changes in linear trends that were described as average annual percentage change (AAPC).ResultsThere were 23,628 DKA presentations in Victoria between 2002 and 2016. For T1D there was an increase in DKA presentations (AAPC + 6.8%) from 2003 to 2016 and for T2D there was a decline from 2003 to 2011 (APC − 3.5%), increase from 2011 to 2014 (APC + 38.5%), and a decrease from 2014 to 2016 (APC − 20.9%). Length of stay was longer for people with T2D than T1D (P < 0.001) and the mortality rate was 0.51% for the study period.ConclusionsDKA rates increased for T2D from 2011 to 2014 which correlates with the introduction of sodium glucose-linked transport protein 2 inhibitors. However, the aetiology for the observed increase in T1D from 2002 to 2016 remains unknown.

Federal Impacts on Buprenorphine Prescribing in Washington State, 2012 to 2022.

Objectives. To evaluate changes in monthly buprenorphine dispensation associated with federal prescribing policies in Washington State from 2012 to 2022. Methods. We conducted an interrupted time series analysis comparing monthly buprenorphine prescriptions dispensed per 1000 population after the Comprehensive Addiction and Recovery Act (CARA), Substance Use-Disorder Prevention That Promotes Opioid Recovery and Treatment for Patients and Communities Act (SUPPORT), and new prescribing rules during the COVID-19 pandemic. Buprenorphine formulated for opioid use disorder was included from the Washington State Prescription Monitoring Program. A log-linear autoregressive model measured linear trend changes. Results. Physician prescribing increased by 1.63% (95% confidence interval [CI] = 1.41%, 1.85%) per month after CARA with sustained declines after SUPPORT. Nurse practitioner (NP) prescribing increased by 19.48% (95% CI = 18.8%, 20.16%) per month after CARA with physician assistants (PAs) showing similar trends. Following the implementation of SUPPORT, NP and PA trends continued to increase at a reduced growth rate of 3.96% (95% CI = 2.01%, 5.94%) and 1.87% (95% CI = 0.56%, 3.19%), respectively. No prescribers experienced increases during the COVID-19 pandemic. Conclusions. CARA nearly tripled the buprenorphine prescribing rate. The SUPPORT Act initiated sustained declines for physician prescribing, and the COVID-19 period reversed gains for PAs and NPs. The current opioid crisis requires expanded efforts in Washington State. (Am J Public Health. 2024;114(7):696-704. https://doi.org/10.2105/AJPH.2024.307649).

Trends of long-term fluctuations of atmospheric humidification of the growing season in the steppe zone of Northern Kazakhstan

Agriculture is an important industry in Kazakhstan that ensures the stability of economic development. Within the northern regions of the republic, crop production received special development.The relevance of studying the impact of long-term fluctuations in precipitation on crop yields increases taking into account the projected trends in climate change in the modern period. The high natural heat supply of the territory during the growing season, along with the low availability of moisture resources, is a deterrent to the intensive development of the agro-industrial complex. The territory of Northern Kazakhstan as a whole is characterized by insufficient humidification during the warm period. However, there are wet years with rare recurrence, when moisture can be increased. The article considers the peculiarities of the change in the amount of atmospheric precipitation of the growing season for the long-term period 1961-2020 years according to weather stations located within the steppe zone of Northern Kazakhstan. The degree of aridization of territories was established on the basis of an analysis of the nature of changes in linear trends over different intervals.

Detecting linear trend changes in data sequences

We propose TrendSegment, a methodology for detecting multiple change-points corresponding to linear trend changes in one dimensional data. A core ingredient of TrendSegment is a new Tail-Greedy Unbalanced Wavelet transform: a conditionally orthonormal, bottom-up transformation of the data through an adaptively constructed unbalanced wavelet basis, which results in a sparse representation of the data. Due to its bottom-up nature, this multiscale decomposition focuses on local features in its early stages and on global features next which enables the detection of both long and short linear trend segments at once. To reduce the computational complexity, the proposed method merges multiple regions in a single pass over the data. We show the consistency of the estimated number and locations of change-points. The practicality of our approach is demonstrated through simulations and two real data examples, involving Iceland temperature data and sea ice extent of the Arctic and the Antarctic. Our methodology is implemented in the R package trendsegmentR, available from CRAN.

Temporal trends in non-traumatic lower extremity amputations (LEAs) and their association with 12-month mortality in people with diabetes, 2004–2016

AimsTo assess trends in hospital admissions for non-traumatic lower extremity amputations (LEAs) and for mortality following LEAs in adult patients with type 1 diabetes (T1DM) or type 2 diabetes (T2DM) admitted to hospitals in Victoria, Australia during 2004–2016. MethodsUsing hospital discharge data, we calculated age- and sex- adjusted admission rates for incident cases of any LEA, minor LEAs, major LEAs and 12-month mortality following any LEAs for patients according to diabetes type. Joinpoint regression analysis was used to identify changes in linear trends that were described as average annual percentage change (AAPC). ResultsSignificant declines in rates of admission for any LEA (AAPC −4.9), minor LEAs (−3.0 %) and major LEAs (AAPC -11.5 %) were seen for patients with T2DM. Overall, admission rates for any LEA did not significantly change for patients with T1DM during 2004 and 2016, however, we detected a significant rise in admissions for any LEAs (AAPC +5.1) in female patients with T1DM. This increase was most prominent in younger (<60 years) patients undergoing minor LEAs. During 2009–2016, younger patients with type 1 DM, regardless of sex, also experienced significant increases in admissions for any LEA (AAPC +14) and major LEAs (AAPC +15). Mortality associated with LEAs in T2DM declines, with a 12-month mortality rate of 6.3 %) associated with LEAs in T2M decline (AAPC -4.2 %) whereas rates for T1DM remained stable (1.9 %) during 2004–2016. ConclusionsThere were significant differences in LEA hospital admission trends by type of diabetes, age and sex. The decline in LEAs and its associated mortality is welcome news for patients with T2DM. However, reasons for the increase in LEAs in younger patients with T1DM remain to be determined.

Trend change estimation for interrupted time series with heteroscedastic and autocorrelated errors: application in syphilis occurrences in Brazil

The impact evaluation of exogenous policies over time is of great importance in several areas. Unfortunately, an adequate time-series analysis has not always been taken into account in the literature, mainly in health problems. When regression models are used in the known interrupted time-series approach, the required error assumptions are in general neglected. Specifically, usual linear segmented regression (lmseg) models are not adequate when the errors have nonconstant variance and serial correlation. To instigate the correct use of intervention analysis, we present a simple approach extending a linear model with log-linear variance (lmvar) to estimate linear trend changes under heteroscedastic errors (lmsegvar). When the errors are autocorrelated, the Cochrane-Orcutt (CO) modification is implemented to correct the estimated parameters. As an application, we estimate the impact in temporal trend of the Brazilian Rede Mãe Paranaense (RMP) program in gestational syphilis occurrences in the state of Parana, Brazil. The comparison of the proposed linear segmented model (lmsegvar+CO) modeling both the average and variance, with the usual segmented linear model (lmseg), where just the average is modeled, shows the importance of taking heteroscedasticity and autocorrelation into account.

An adaptive cumulative sum method for monitoring integer-valued time-series data

In this paper, we propose an adaptive CUSUM monitoring method for detecting step and linear trend changes in count-data time-series. The data is represented using a seasonal INGARCH time series model and an exponential smoother is used to estimate level or trend changes in the data in the cumulative-sum (CUSUM) detector. In a simulation study, the proposed approach is compared to existing CUSUM approaches that are tuned for a specific shift size and the ability of the methods to detect step shifts and linear trends is investigated. The application of the proposed method in public health surveillance is demonstrated using a real infectious disease count data set.

Detectability of variation in river flood from satellite images

Floods are major natural disasters that have considerable consequences worldwide. As the frequency and magnitude of flooding are expected to be affected by ongoing climate change, understanding their past changes is important for developing adequate adaptation measures. However, the limited spatiotemporal coverage of flood gauges hinders detection of changes in flooding, particularly in poorly gauged regions. Here, we propose a method using surface water data of river floodplain inundation as a proxy of the magnitude and frequency of flooding. Surface water data − Aqua Monitor which represented the probability linear trend changes in land and water surface area based on 30-m Landsat images between 1984–2000 and 2000–2013 was used in this study. The changes in water surface area over the floodplain obtained from Aqua Monitor showed high correspondence with historical trends observed or simulated annual maximum daily discharge, indicating the potential to detect changes in frequency and magnitude of flood from satellite data. In regions where changes could be measured with sufficient satellite images, 29% showed an increase in water surface area in the flood plain, 41% showed a decrease, and 30% showed small or no changes.

Are shifts in species distribution triggered by climate change? A swordfish case study

Species shifts due to climate change are being recorded and reported worldwide. However, the accurate estimation and causal attribution of species shifts using spatial distribution indicators, such as the center of gravity, is challenging. This is particularly problematic for commercially exploited marine species with data from research surveys, commercial fisheries or other data collection methods that are not recorded homogeneously over time and space. Here, we propose a new framework to ascertain whether the changes in the spatial distribution of species are due to changes in habitat conditions, fishing activity or other factors. This approach is developed to help elucidate the main drivers of species shifts and it is based upon the comparison of historical trends in species distribution shifts among raw data and modeled: i) fishing effort, ii) population occurrence and abundance, iii) habitat, and iv) spatio-temporal reconstruction of the species distribution. We apply this new methodology to the case study of swordfish populations worldwide. On a global scale, 2 out of 6 stocks of swordfish shifted latitudinally during 1958–2004. Of those two, only the Mediterranean stock was associated with a linear trend change of its habitat. In two other stocks, the latitudinal center of gravity of populations occurrence varies following their habitats’ interannual variability; however, this shift is not linear. We further developed a worldwide habitat suitability model for swordfish and projected its distribution and abundance into the future under the RCP8.5 climate change scenario, the highest greenhouse gas concentration scenario, by the end of the century. Future projections estimate an overall swordfish decrease of 22% in CPUE (catch per unit of effort), with substantial decreases in most tropical areas, and a slight increase in its distribution range limits, both in the north and southern hemispheres.

Abstract WP292: Changing Landscape of Stroke Systems of Care: Increase in Inter Hospital Transfer in the United States

Purpose: Interhospital transfer is necessary to facilitate endovascular therapy (EVT) for patients with emergent large vessel occlusion (ELVO) who present to nonendovascular centers. We hypothesized that interhospital transfer would accelerate following 2014 pivotal randomized controlled trials (RCTs) demonstrating benefits of EVT. Methods: We analyzed trend of interhospital transfer for EVT using Get With The Guideline (GWTG)-Stroke from January 2012 to September 2016. Analyses of transfer-in trend for the hospitals consistently providing EVT were restricted to hospitals with &gt;1 EVT/quarter in last 4 study quarters (250 sites). We analyzed trend of interhospital transfer for all ischemic stroke (IS) patients and following subgroup: NIHSS ≥6 and arrival to the EVT-providing hospital within 7 hours of last known well. Results: During the study period 31425 patients received EVT. Transfer-in EVT cases increased from 334 to 912 from Q3 2014 to Q3 2016 (p&lt;0.001 for change in linear trend, Figure 1A). Interhospital transfer for EVT is common (44% in Q3 2016) and increasing proportion of IS patients are arriving to EVT-providing hospitals as transfers, especially among the subgroup of NIHSS ≥6 and arrival to the EVT-providing hospital within 7 hours of last known well (Figure 1B). Since RCT announcement, transfer-in patients receive EVT at a significantly higher rate (5.2% in Q3 2014 vs. 10.8% in Q3 2016, Figure 1C). Hospitals with a higher % transfer-in EVT (comparing top quartile to bottom quartile) were more likely to have more beds and be in an urban location, with comprehensive stroke center certification and higher annual EVT volumes. Conclusions: Interhospital transfer of IS patients has accelerated markedly in the past two years, highlighting the need to develop protocols and quality metrics to ensure efficient systems of care for this subset of patients.

Separating out the influence of climatic trend, fluctuations, and extreme events on crop yield: a case study in Hunan Province, China

Separating out the influence of climatic trend, fluctuations and extreme events on crop yield is of paramount importance to climate change adaptation, resilience, and mitigation. Previous studies lack systematic and explicit assessment of these three fundamental aspects of climate change on crop yield. This research attempts to separate out the impacts on rice yields of climatic trend (linear trend change related to mean value), fluctuations (variability surpassing the “fluctuation threshold” which defined as one standard deviation (1 SD) of the residual between the original data series and the linear trend value for each climatic variable), and extreme events (identified by absolute criterion for each kind of extreme events related to crop yield). The main idea of the research method was to construct climate scenarios combined with crop system simulation model. Comparable climate scenarios were designed to express the impact of each climate change component and, were input to the crop system model (CERES-Rice), which calculated the related simulated yield gap to quantify the percentage impacts of climatic trend, fluctuations, and extreme events. Six Agro-Meteorological Stations (AMS) in Hunan province were selected to study the quantitatively impact of climatic trend, fluctuations and extreme events involving climatic variables (air temperature, precipitation, and sunshine duration) on early rice yield during 1981–2012. The results showed that extreme events were found to have the greatest impact on early rice yield (−2.59 to −15.89%). Followed by climatic fluctuations with a range of −2.60 to −4.46%, and then the climatic trend (4.91–2.12%). Furthermore, the influence of climatic trend on early rice yield presented “trade-offs” among various climate variables and AMS. Climatic trend and extreme events associated with air temperature showed larger effects on early rice yield than other climatic variables, particularly for high-temperature events (−2.11 to −12.99%). Finally, the methodology use to separate out the influences of the climatic trend, fluctuations, and extreme events on crop yield was proved to be feasible and robust. Designing different climate scenarios and feeding them into a crop system model is a potential way to evaluate the quantitative impact of each climate variable.

Supply-Side Disruption in Cocaine Production Associated With Cocaine-Related Maternal and Child Health Outcomes in the United States.

To investigate the effects of precursor chemical regulation aimed at reducing cocaine production on cocaine-related maternal and newborn hospital stays in the United States. We analyzed monthly counts of maternal and neonatal stays from January 2002 through December 2013 by using a quasi-experimental interrupted time series design. We estimated the preregulation linear trend, postregulation change in linear trend, and abrupt change in level. The number of monthly cocaine-related maternal and neonatal stays decreased by 221 and 128 stays, respectively, following the cocaine precursor regulation change. We also observed a further decline in per-month maternal and neonatal stays of 18 and 8 stays, respectively. A supply-side disruption in the United States cocaine market was associated with reduced hospital stays for 2 vulnerable populations: pregnant women and newborns. Results support findings that federal precursor regulation can positively reduce cocaine availability in the United States.

Can the provision of a home help service for the elderly population reduce the incidence of fall-related injuries? A quasi-experimental study of the community-level effects on hospital admissions in Swedish municipalities

BackgroundFall-related injuries are a global public health problem, especially in elderly populations. The effect of an intervention aimed at reducing the risk of falls in the homes of community-dwelling elderly...

Location of Usual Source of Care among Children and Adolescents in the United States, 1997-2013

To examine national trends in the percentage of children whose usual source of care is at a clinic, health center, or hospital outpatient department (hereafter "clinics") and whether trends differ by sociodemographic subpopulations. Analysis of serial, cross-sectional, nationally representative in-person household surveys, the 1997-2013 National Health Interview Surveys, was conducted to identify children with a usual source of care (n = 190,571), and the percentage receiving that care in a clinic. We used joinpoint regression to identify changes in linear trends, and logistic regression with predictive margins to obtain per-year changes in percentages, both unadjusted and adjusted for sociodemographic factors. Interaction terms in logistic regressions were used to assess whether trends varied by sociodemographic subgroups. Of all children with a usual source of care, the percentage receiving that care in a clinic declined 0.44 percentage points per year (P < .001) from 22.97% in 1997 to 19.31% in 2002. Thereafter, it increased approximately 0.57 percentage points per year (P < .001), reaching 26.1% in 2013. Trends for some sociodemographic subgroups varied from these overall trends. No changes were observed between 2003 and 2013 for non-Hispanic black and Medicaid/State Children's Health Insurance Program insured children. This study shows that, although the percentage of children with a usual source of care in a clinic declined between 1997 and 2002, it has steadily increased since that time.

Variability of atmospheric aerosol optical depth over the Northern Tian Shan

Presented are the data of measurements of aerosol optical depth (AOD) of the atmosphere at the wavelength of 500 nm for the period from 1984 to 2009 at Issyk Kul monitoring station located in the central part of Eurasia. The decrease in AOD by about 4.3% took place during the measurement period. Revealed are the seasonal variations, linear trends, and periods of AOD increase associated with volcanic eruptions. The spectral analysis of measurement data using the Fourier and wavelet transforms enabled determining the basic characteristics of the constituents of AOD variations. The linear trend changes from positive to negative from 1995 to 2009 that may indicate increase in the amount of aerosol in these years. Proposed is a simple statistical model for describing the temporal variations of AOD.

A type-2 fuzzy-statistical clustering approach for estimating the multiple change points in a process mean with monotonic change

Identifying the real time of the change in a process, recognized as change point problem, simplifies the removal of change causes. In most of the change point models, the existence of different uncertainty levels is either ignored or paid a little attention to. This paper tries to address an appropriate model to estimate the multiple change points in a monotonic change process in an uncertain condition and for a known number of change points. In this regard, a novel set of membership functions and a novel objective function, based on using interval type-2 fuzzy sets, are introduced in a fuzzy-statistical clustering approach. The proposed approach, in addition to the ability of managing various amount of uncertainty, is free from the distribution of the process variables, and in the case of existence, a certain variable distribution, it is independent from it. Finally, extensive simulation studies are conducted to evaluate the performance of the proposed approach in simple step change, multiple step change, and linear trend change in the presence of isotonic change in the process mean. The results are compared with some of the powerful change point approaches.

Estimating the change point of binary profiles in phase II

Identifying the real time change in a process, when an out-of-control signal is given by a control chart is crucial and leads to cost and time savings significantly. There are processes or products whose quality is described by a relationship between a response variable and one or more explanatory variable. This relationship is known as profile in the literature of statistical process control and is modelled by different regression types including logistic regression. This type of profile is used where the response variable follows a binomial distribution. In this paper, a maximum likelihood estimator (MLE) based on regression parameters is developed to find the real time of a step change in logistic regression profiles. Simulation studies are provided to evaluate the performance of the proposed change point estimator under both single step change and linear trend change.

Identifying time of a monotonic change in the fraction nonconforming of a high-quality process

When a signal is detected by control charts, a search begins to identify and eliminate the sources of this signal. Knowing when a process has changed is very helpful for this purpose. The unknown special point that the process changed for the first time is referred to as change point. In this paper, we propose a maximum-likelihood estimator for the behavior model of the process fraction nonconforming in a high-quality process monitored with a cumulative count of conforming (CCC) control chart. We estimate the time of change without requiring the prior knowledge of the change type rather than we assume the type of change present belongs to a family of monotonic changes. Then, we compare the performance of the proposed change point estimator relative to estimators for the process fraction nonconforming change point derived under a single step and a linear trend change assumption. We do this for a number of monotonic change types following a signal from a CCC control chart. Finally, the application of the proposed change point estimator is shown through a real case.

Detection of the Onset of Multiple Sclerosis from SD-OCT Thickness Measurements of the Retinal Nerve Fiber Layer

ABSTRACT The cumulative sum (CUSUM) likelihood ratio detector (discussed in Lai [1995] and Frisen [2003]) can be used to monitor a process level against linear trend changes. In this article we discuss this detector and its relationship to the standard CUSUM, which guards against step changes in the level; provide software for its implementation; and present a case study that uses this method to detect the onset of multiple sclerosis. The thickness of the retinal nerve fiber layer has been suggested as a diagnostic measure for evaluating the progression of multiple sclerosis. Newly improved optical coherence tomography (OCT) instrumentation using scan averaging and alignment with a reference scan has reduced the short-term measurement variability in the retinal nerve fiber layer thickness to an extent that allows the proposed CUSUM likelihood ratio detector to detect clinically relevant changes over time. We show that this procedure detects such changes quickly and performs better than the traditional CUSUM technique that protects against step changes in the level.

Secular Trends in Swedish Hip Fractures 1987–2002

Recently, a leveling off in hip-fracture incidence has been reported in several settings, but the annual number is nonetheless predicted to increase due to the growing elderly population. Using Swedish national data for 1987-2002 for all inpatients 50 years or older, we examined the annual number and incidence of hip fractures and explored age, period, and cohort effects. Age adjustment was done by direct standardization, time-trend analysis by linear regression, changes in linear trends by joinpoint regression, and age-period-cohort effects by log-likelihood estimates in Poisson regression models. Before 1996, the age-standardized hip fracture incidence was stable (0.1% per year [95% confidence interval = -0.2% to 0.5%]), and the annual number of hip fractures increased (2.1% per year [1.8% to 2.4%]). After 1996, both the age-standardized hip fracture incidence (-2.2% per year [-2.8% to -1.6%]) and the number of hip fractures (-0.9% per year [-1.5% to -0.4%]) decreased. The period + cohort effects were more marked among women than men, with a major reduction in hip fracture incidence in subsequent birth cohorts (estimated incidence rate ratio = 2.2 comparing women born 1889-1896 with 1945-1952) or periods (estimated incidence rate ratio = 1.1 comparing women living 1987-1990 with 1999-2002). The age-standardized hip fracture incidence has decreased since 1996, more than counteracting the effects of the aging population and resulting in a decline in the annual number of hip fractures through 2002. The magnitude of the combined period and cohort effects in women seems to be of biologic importance. If this persists into older age, the annual number of hip fractures will be lower than has been projected.