Biases in the estimation of size-dependent mortality models: advantages of a semiparametric approach

2009 ◽  
Vol 39 (8) ◽  
pp. 1430-1443 ◽  
Author(s):  
Ghislain Vieilledent ◽  
Benoît Courbaud ◽  
Georges Kunstler ◽  
Jean-François Dhôte ◽  
James S. Clark
Keyword(s):  
Mortality Rate ◽  
Picea Abies ◽  
Abies Alba ◽  
Mortality Data ◽  
Strongly Nonlinear ◽  
Semiparametric Approach ◽  
Mortality Models ◽  
Large Trees ◽  
Parametric Functions ◽  
Related Mortality

Mortality rate is thought to show a U-shape relationship to tree size. This shape could result from a decrease of competition-related mortality as diameter increases, followed by an increase of senescence and disturbance-related mortality for large trees. Modeling mortality rate as a function of diameter is nevertheless difficult, first because this relationship is strongly nonlinear, and second because data can be unbalanced, with few observations for large trees. Parametric functions, which are inflexible and sensitive to the distribution of observations, tend to introduce biases in mortality rate estimates. In this study we use mortality data for Abies alba Mill. and Picea abies (L.) Karst. to demonstrate that mortality rate estimates for extreme diameters were biased when using classical parametric functions. We then propose a semiparametric approach allowing a more flexible relationship between mortality and diameter. We show that the relatively shade-tolerant A. alba has a lower annual mortality rate (2.75%) than P. abies (3.78%) for small trees (DBH <15 cm). Picea abies, supposedly more sensitive to bark beetle attacks and windthrows, had a higher mortality rate (up to 0.46%) than A. alba (up to 0.30%) for large trees (DBH ≥50 cm).

scholarly journals NEIGHBOURING PREDICTION FOR MORTALITY

2021 ◽  
pp. 1-30
Author(s):  
Chou-Wen Wang ◽  
Jinggong Zhang ◽  
Wenjun Zhu
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Mortality Rate ◽  
Prediction Model ◽  
Mortality Data ◽  
Nonlinear Structure ◽  
Mortality Forecasting ◽  
Mortality Models ◽  
Forecasting Performance ◽  
Deep Learning Model

ABSTRACT We propose a new neighbouring prediction model for mortality forecasting. For each mortality rate at age x in year t, mx,t, we construct an image of neighbourhood mortality data around mx,t, that is, Ꜫ mx,t (x1, x2, s), which includes mortality information for ages in [x-x1, x+x2], lagging k years (1 ≤ k ≤ s). Combined with the deep learning model – convolutional neural network, this framework is able to capture the intricate nonlinear structure in the mortality data: the neighbourhood effect, which can go beyond the directions of period, age, and cohort as in classic mortality models. By performing an extensive empirical analysis on all the 41 countries and regions in the Human Mortality Database, we find that the proposed models achieve superior forecasting performance. This framework can be further enhanced to capture the patterns and interactions between multiple populations.

Perbandingan Linieritas Dalam Pendeteksian Faktor-Faktor Yang Mempengaruhi Angka Kematian Bayi Di Provinsi Aceh

2019 ◽  
Vol 2 (2) ◽  
Author(s):  
Desfira Ahya ◽  
Inas Salsabila ◽  
Miftahuddin
Keyword(s):  
Mortality Rate ◽  
Infant Mortality ◽  
Linear Model ◽  
Health Workers ◽  
Additive Model ◽  
Infant Mortality Rate ◽  
Mortality Data ◽  
Important Indicator ◽  
Penalized Spline ◽  
Aceh Province

Angka Kematian Bayi/ Infant Mortality Rate (IMR) merupakan indikator penting dalam mengukur keberhasilan pengembangan kesehatan. Nilai IMR juga dapat digunakan untuk mengetahui tingkat kesehatan ibu, kondisi kesehatan lingkungan dan secara umum, tingkat pengembangan sosio-ekonomi masyarakat. Penelitian ini bertujuan untuk memperoleh model IMR terbaik menggunakan tiga pendekatan: Model Linear, Model Linear Tergeneralisir dan Model Aditif Tergeneralisir dengan basis P-spline. Sebagai tambahan, berdasarkan model tersebut akan terlihat variabel yang mempengaruhi tingkat kematian bayi di provinsi Aceh. Penelitian ini menggunakan data jumlah kematian bayi di tahun 2013-2015. Data dalam penelitian ini diperoleh dari Profil Kesehatan Aceh. Hasil menunjukkan bahwa model terbaik dalam menjelaskan angka kematian bayi di provinsi Aceh tahun 2013-2015 ialah Model Linear Tergeneralisir dengan basis P-spline menggunakan parameter penghalusan 100 dan titik knots 8. Faktor yang sangat mempengaruhi angka kematian ialah jumlah pekerja yang sehat.   Infant mortality rate (IMR) is an important indicator in measuring the success of health development. IMR also can be used to knowing the level of maternal health, environmental health conditions and generally the level of socio-economic development in community. This research aims to get the best model of infant mortality data using three approaches: Linear Model, Generalized Linear Model and Generalized Additive Model with Penalized Spline (P-spline) base. In addition, based on the model can be seen the variables that affect to infant mortality in Aceh Province. This research uses data number of infant mortality in Aceh Province period 2013-2015. The data in this research were obtained from Aceh’s Health Profile. The results show that the best model can be explain infant mortality rate in Aceh Province period 2013-2015 is GAM model with P-spline base using smoothing parameter 100 and knots 8. Factor that high effect to infant mortality is number of health workers.

scholarly journals Suitability of sugar, amino acid, and inorganic ion compositions to distinguish fir and spruce honey

2021 ◽  
Author(s):  
Basel Shaaban ◽  
Victoria Seeburger ◽  
Annette Schroeder ◽  
Gertrud Lohaus
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Picea Abies ◽  
Multivariate Analyses ◽  
Abies Alba ◽  
Inorganic Ions ◽  
Scale Insects ◽  
Inorganic Ion ◽  
Plant Feeding ◽  
Different Types

AbstractHoneydew honey is produced by bees from excretions of plant-feeding insects, such as aphids and scale insects. Honeydew on conifers, like fir (Abies alba) or spruce (Picea abies), is produced by different species of the genera Cinara and Physokermes. This means that honeydew honey can stem from different botanical as well as zoological origins, but so far it is not possible to clearly distinguish the different types of honeys. In the attempt to identify distinguishing markers, 19 sugars, 25 amino acids and 9 inorganic ions were quantified in three groups of honeydew honey (fir/Cinara, spruce/Cinara and spruce/Physokermes) with 20 honey samples each. It could be demonstrated that the contents of isomaltose, raffinose, erlose, two undefined oligosaccharides, several amino acids, sulfate, and phosphate differed significantly between the three groups of honey. Furthermore, multivariate analyses resulted in a separation of spruce/Physokermes honey from spruce- or fir/Cinara honey due to its higher contents of phosphate, sulfate, erlose and two undefined oligosaccharides. Moreover, the amino acid composition and the isomaltose as well as the raffinose contents proved useful in the distinction between fir/Cinara and spruce/Cinara honey. In sum, the contents of sugars, amino acids, and inorganic ions in German fir and spruce honeys provide useful information about the botanical and zoological origin of honeydew honeys.

scholarly journals Impact of Relaxing Covid-19 Social Distancing Measures on Rural North Wales: A Simulation Analysis

2020 ◽  
Vol 8 ◽  
Author(s):  
Rhodri P. Hughes ◽  
Dyfrig A. Hughes
Keyword(s):  
Simulation Analysis ◽  
Model Averaging ◽  
Incidence Rates ◽  
Mortality Data ◽  
Rural Regions ◽  
Social Distancing ◽  
North Wales ◽  
The Uk ◽  
Sigmoidal Growth ◽  
Related Mortality

Background: Social distancing policies aimed to limit Covid-19 across the UK were gradually relaxed between May and August 2020, as peak incidences passed. Population density is an important driver of national incidence rates; however peak incidences in rural regions may lag national figures by several weeks. We aimed to forecast the timing of peak Covid-19 mortality rate in rural North Wales.Methods: Covid-19 related mortality data up to 7/5/2020 were obtained from Public Health Wales and the UK Government. Sigmoidal growth functions were fitted by non-linear least squares and model averaging used to extrapolate mortality to 24/8/2020. The dates of peak mortality incidences for North Wales, Wales and the UK; and the percentage of predicted mortality at 24/8/2020 were calculated.Results: The peak daily death rates in Wales and the UK were estimated to have occurred on the 14/04/2020 and 15/04/2020, respectively. For North Wales, this occurred on the 07/05/2020, corresponding to the date of analysis. The number of deaths reported in North Wales on 07/05/2020 represents 33% of the number predicted to occur by 24/08/2020, compared with 74 and 62% for Wales and the UK, respectively.Conclusion: Policies governing the movement of people in the gradual release from lockdown are likely to impact significantly on areas–principally rural in nature–where cases of Covid-19, deaths and immunity are likely to be much lower than in populated areas. This is particularly difficult to manage across jurisdictions, such as between England and Wales, and in popular holiday destinations.

scholarly journals Antiplatelet Agents for Cancer Prevention: Current Evidences and Continuing Controversies

Cancers ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 1639 ◽  
Author(s):  
Corinne Frere ◽  
Manon Lejeune ◽  
Pierre Kubicek ◽  
Dorothée Faille ◽  
Zora Marjanovic ◽  
...  
Keyword(s):  
Clinical Evidence ◽  
Task Force ◽  
Cardiovascular Prevention ◽  
Antiplatelet Agents ◽  
Mortality Data ◽  
Low Dose Aspirin ◽  
The Us ◽  
Secondary Analyses ◽  
Prevention Trials ◽  
Related Mortality

Over the past two decades, aspirin has emerged as a promising chemoprotective agent to prevent colorectal cancer (CRC). In 2016, the mounting evidence supporting its chemoprotective effect, from both basic science and clinical research, led the US Preventive Services Task Force to recommend regular use of low-dose aspirin in some subgroups of patients for whom the benefits are deemed to outweigh the risks. In contrast, data on the chemoprotective effect of aspirin against other cancers are less clear and remain controversial. Most data come from secondary analyses of cardiovascular prevention trials, with only a limited number reporting cancer outcomes as a prespecified endpoint, and overall unclear findings. Moreover, the potential chemoprotective effect of aspirin against other cancers has been recently questioned with the publication of 3 long-awaited trials of aspirin in the primary prevention of cardiovascular diseases reporting no benefit of aspirin on overall cancer incidence and cancer-related mortality. Data on the chemoprotective effects of other antiplatelet agents remain scarce and inconclusive, and further research to examine their benefit are warranted. In this narrative review, we summarize current clinical evidence and continuing controversies on the potential chemoprotective properties of antiplatelet agents against cancer.

scholarly journals The spatial epidemiology of alcohol-related mortality among the Czech adult population

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
L Kazmer ◽  
I Kulhanova ◽  
M Lustigova
Keyword(s):  
Local Community ◽  
Spatial Epidemiology ◽  
Adult Population ◽  
Age Groups ◽  
Health Determinants ◽  
Mortality Data ◽  
Annual Data ◽  
Cross Sectional ◽  
Inequalities In Health ◽  
Related Mortality

Abstract Background In Czechia, alcohol-induced deaths account for a significant portion of preventable mortality. As inequalities in health are both socially and spatially determined, the paper aims at the detailed examination of socio-geographic inequalities of this phenomenon. Methods The 2011-2015 annual data on both ICD-10 cause-specific deaths (K70; F10; X45/64; Y15) and mid-year population were obtained from the official Czech registries - the data were cross-classified by gender, 5-year age-groups, and permanent residence (N = 6,302 small area spatial units). The selected socio-demographic indicators (education, unemployment, religious population) from the Czech 2011 Census were spatially merged to the mortality dataset. From the data on education and unemployment, composite deprivation index (DI) was derived. In the adult population aged 25+, the age-standardised mortality ratios (SMR) were computed for each of the spatial units, separately by genders. The SMRs were spatially modelled by the Besag-York-Mollié (BYM) autoregressive approach, applying a fully bayesian framework integrated within the INLA R-package. The study applied cross-sectional design and employed ecological regression conducted on observational data. Results Compared to the Czech average, the highest SMRs were located in the historical regions of Moravia [SMR=1.15; 95%CI: 1.11-1.19] and Silesia [SMR=1.59; 95%CI: 1.52-1.66]. The SMRs were significantly correlated with DI among males [Rel.Risk=1.15; 95%CI: 1.11-1.19], and with religiousness rate among females [Rel.Risk=0.83; 95%CI: 0.77-0.90]. Conclusions Significant socio-geographic inequalities were detected, particularly with respect to the Czech historical regions. Among males, higher mortality was associated with a structural deprivation. Among females, protective effect of religiousness rate was found to be significant. The results highlight an importance of both socially and spatially integrated efforts for public health promotion. Key messages The inequalities in health are both socially and spatially contextualised. The paper presents robust empirical evidence in favour of the proposition, as examined on alcohol-related mortality data. The health determinants may be gender sensitive. Males might be more responsive to a structural disadvantage. Among females, cultural factors related to a local community might be more 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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