scholarly journals Nonparametric trend estimation in functional time series with application to annual mortality rates

Biometrics ◽  
2020 ◽  
Author(s):  
Israel Martínez‐Hernández ◽  
Marc G. Genton
Keyword(s):  
Time Series ◽  
Mortality Rates ◽  
Trend Estimation ◽  
Functional Time Series ◽  
Annual Mortality

scholarly journals FORECASTING MULTIPLE FUNCTIONAL TIME SERIES IN A GROUP STRUCTURE: AN APPLICATION TO MORTALITY

2020 ◽  
Vol 50 (2) ◽  
pp. 357-379 ◽  
Author(s):  
Han Lin Shang ◽  
Steven Haberman
Keyword(s):  
Time Series ◽  
Group Structure ◽  
Forecast Accuracy ◽  
Mortality Rates ◽  
Series Method ◽  
Functional Time Series ◽  
Forecast Combinations ◽  
Time Series Method ◽  
Mortality Forecasts ◽  
The Impact

AbstractWhen modelling subnational mortality rates, we should consider three features: (1) how to incorporate any possible correlation among subpopulations to potentially improve forecast accuracy through multi-population joint modelling; (2) how to reconcile subnational mortality forecasts so that they aggregate adequately across various levels of a group structure; (3) among the forecast reconciliation methods, how to combine their forecasts to achieve improved forecast accuracy. To address these issues, we introduce an extension of grouped univariate functional time-series method. We first consider a multivariate functional time-series method to jointly forecast multiple related series. We then evaluate the impact and benefit of using forecast combinations among the forecast reconciliation methods. Using the Japanese regional age-specific mortality rates, we investigate 1–15-step-ahead point and interval forecast accuracies of our proposed extension and make recommendations.

scholarly journals Forecasting Age-Specific Brain Cancer Mortality Rates Using Functional Data Analysis Models

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Keshav P. Pokhrel ◽  
Chris P. Tsokos
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
State Space ◽  
Functional Data Analysis ◽  
Brain Cancer ◽  
Functional Data ◽  
Cancer Mortality ◽  
Mortality Rates ◽  
Exponential Smoothing ◽  
Functional Time Series

Incidence and mortality rates are considered as a guideline for planning public health strategies and allocating resources. We apply functional data analysis techniques to model age-specific brain cancer mortality trend and forecast entire age-specific functions using exponential smoothing state-space models. The age-specific mortality curves are decomposed using principal component analysis and fit functional time series model with basis functions. Nonparametric smoothing methods are used to mitigate the existing randomness in the observed data. We use functional time series model on age-specific brain cancer mortality rates and forecast mortality curves with prediction intervals using exponential smoothing state-space model. We also present a disparity of brain cancer mortality rates among the age groups together with the rate of change of mortality rates. The data were obtained from the Surveillance, Epidemiology and End Results (SEER) program of the United States. The brain cancer mortality rates, classified under International Classification Disease code ICD-O-3, were extracted from SEER*Stat software.

scholarly journals Mortality in Dementia from 1996 to 2015: A National Registry-Based Cohort Study

2021 ◽  
Vol 79 (1) ◽  
pp. 289-300
Author(s):  
Lærke Taudorf ◽  
Ane Nørgaard ◽  
Gunhild Waldemar ◽  
Thomas Munk Laursen
Keyword(s):  
Elderly People ◽  
Age Groups ◽  
Mortality Rates ◽  
Similar Rate ◽  
National Registry ◽  
Healthcare Data ◽  
Appropriate Care ◽  
People With Dementia ◽  
Rate Ratios ◽  
Annual Mortality

Background: It remains unclear whether the increased focus on improving healthcare and providing appropriate care for people with dementia has affected mortality. Objective: To assess survival and to conduct a time trend analysis of annual mortality rate ratios (MRR) of dementia based on healthcare data from an entire national population. Methods: We assessed survival and annual MRR in all residents of Denmark ≥65 years from 1996–2015 using longitudinal registry data on dementia status and demographics. For comparison, mortality and survival were calculated for acute ischemic heart disease (IHD) and cancer. Results: The population comprised 1,999,366 people (17,541,315 person years). There were 165,716 people (529,629 person years) registered with dementia, 131,321 of whom died. From 1996–2015, the age-adjusted MRR for dementia declined (women: 2.76 to 2.05; men: 3.10 to 1.99) at a similar rate to elderly people without dementia. The sex-, age-, and calendar-year-adjusted MRR was 2.91 (95%CI: 2.90–2.93) for people with dementia. MRR declined significantly more for acute IHD and cancer. In people with dementia, the five-year survival for most age-groups was at a similar level or lower as that for acute IHD and cancer. Conclusion: Although mortality rates declined over the 20-year period, MRR stayed higher for people with dementia, while the MRR gap, compared with elderly people without dementia, remained unchanged. For the comparison, during the same period, the MRR gap narrowed between people with and without acute IHD and cancer. Consequently, initiatives for improving health and decreasing mortality in dementia are still highly relevant.

Abstract P261: Intensive Systolic Blood Pressure Lowering Will Prevent Over 100,000 Deaths Annually

Hypertension ◽  
2016 ◽  
Vol 68 (suppl_1) ◽  
Author(s):  
Holly Kramer ◽  
Adam Bress ◽  
Srinivasan Beddhu ◽  
Paul Muntner ◽  
Richard S Cooper
Keyword(s):  
Blood Pressure ◽  
Mortality Rate ◽  
Systolic Blood Pressure ◽  
Mortality Rates ◽  
Mortality Data ◽  
Blood Pressure Lowering ◽  
Cvd Risk ◽  
Pressure Lowering ◽  
Annual Mortality ◽  
The U.S

Background: The Systolic Blood Pressure Intervention Trial (SPRINT) trial randomized 9,361 adults aged ≥50 years at high cardiovascular disease (CVD) risk without diabetes or stroke to intensive systolic blood pressure (SBP) lowering (≤120 mmHg) or standard SBP lowering (≤140 mmHg). After a median follow up of 3.26 years, all-cause mortality was 27% (95% CI 40%, 10%) lower with intensive SBP lowering. We estimated the potential number of prevented deaths with intensive SBP lowering in the U.S. population meeting SPRINT criteria. Methods: SPRINT eligibility criteria were applied to the National Health and Nutrition Examination Survey 1999-2006, a representative survey of the U.S. population, linked with the mortality data through December 2011. Eligibility included (1) age ≥50 years with (2) SBP 130-180 mmHg depending on number of antihypertensive classes being taken, and (3) presence of ≥1 CVD risk conditions (history of coronary heart disease, estimated glomerular filtration rate (eGFR) 20 to 59 ml/min/1.73 m 2 , 10-year Framingham risk score ≥15%, or age ≥75 years). Adults with diabetes, stroke history, >1 g/day proteinuria, heart failure, on dialysis, or eGFR<20 ml/min/1.73m 2 were excluded. Annual mortality rates for adults meeting SPRINT criteria were calculated using Kaplan-Meier methods and the expected reduction in mortality rates with intensive SBP lowering in SPRINT was used to determine the number of potential deaths prevented. Analyses accounted for the complex survey design. Results: An estimated 18.1 million U.S. adults met SPRINT criteria with 7.4 million taking blood pressure lowering medications. The mean age was 68.6 years and 83.2% and 7.4% were non-Hispanic white and non-Hispanic black, respectively. The annual mortality rate was 2.2% (95% CI 1.9%, 2.5%) and intensive SBP lowering was projected to prevent 107,453 deaths per year (95% CI 45,374 to 139,490). Among adults with SBP ≥145 mmHg, the annual mortality rate was 2.5% (95% CI 2.1%, 3.0%) and intensive SBP lowering was projected to prevent 60,908 deaths per year (95% CI 26, 455 to 76, 792). Conclusions: We project intensive SBP lowering could prevent over 100,000 deaths per year of intensive treatment.

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