A study of the incidence and mortality hazard rate of myocardial infarction in Tromsø
This thesis uses data from the Tromsø Study and weather data from the Norwegian Meteorological Institute to study the mortality hazard rate and incidence rate of myocardial infarction (MI) in Tromsø using a latent Gaussian modelling framework. Inference is performed using integrated nested Laplace a...
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UiT Norges arktiske universitet
2019
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Online Access: | https://hdl.handle.net/10037/16090 |
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ftunivtroemsoe:oai:munin.uit.no:10037/16090 2023-05-15T18:34:20+02:00 A study of the incidence and mortality hazard rate of myocardial infarction in Tromsø Skjold, Gunnhild 2019-05-31 https://hdl.handle.net/10037/16090 eng eng UiT Norges arktiske universitet UiT The Arctic University of Norway https://hdl.handle.net/10037/16090 openAccess Copyright 2019 The Author(s) VDP::Matematikk og Naturvitenskap: 400::Matematikk: 410::Statistikk: 412 VDP::Mathematics and natural science: 400::Mathematics: 410::Statistics: 412 Integrated nested Laplace approximations applied statistics Latent Gaussian models MAT-3907 Master thesis Mastergradsoppgave 2019 ftunivtroemsoe 2021-06-25T17:56:49Z This thesis uses data from the Tromsø Study and weather data from the Norwegian Meteorological Institute to study the mortality hazard rate and incidence rate of myocardial infarction (MI) in Tromsø using a latent Gaussian modelling framework. Inference is performed using integrated nested Laplace approximations (INLA). This thesis presents the datasets and describes the modelling and computational framework, before analysis is performed. To study the mortality hazard rate after MI, a Cox proportional hazards model has been implemented. A model without a seasonal effect with sex as a stratum variable was deemed the best fit. The results show an increased risk in the month after a MI. After the first month, the risk drops, before it increases with age. The mortality hazard rate is slightly higher for men than for women. To study the change in the rate of MI during the time of the study, a Bayesian age-period-cohort model has been implemented. The model only includes the men of the study. This model studies the rate of MI on three different time scales: age, period, and cohort. The effects from age, period, and cohort are not directly identifiable. However, second differences describing the curvature and relative risk ratios are identifiable, as is the overall rate. The results show the incidence rate of MI decreasing with period, and increasing with age. Master Thesis Tromsø University of Tromsø: Munin Open Research Archive Laplace ENVELOPE(141.467,141.467,-66.782,-66.782) Tromsø |
institution |
Open Polar |
collection |
University of Tromsø: Munin Open Research Archive |
op_collection_id |
ftunivtroemsoe |
language |
English |
topic |
VDP::Matematikk og Naturvitenskap: 400::Matematikk: 410::Statistikk: 412 VDP::Mathematics and natural science: 400::Mathematics: 410::Statistics: 412 Integrated nested Laplace approximations applied statistics Latent Gaussian models MAT-3907 |
spellingShingle |
VDP::Matematikk og Naturvitenskap: 400::Matematikk: 410::Statistikk: 412 VDP::Mathematics and natural science: 400::Mathematics: 410::Statistics: 412 Integrated nested Laplace approximations applied statistics Latent Gaussian models MAT-3907 Skjold, Gunnhild A study of the incidence and mortality hazard rate of myocardial infarction in Tromsø |
topic_facet |
VDP::Matematikk og Naturvitenskap: 400::Matematikk: 410::Statistikk: 412 VDP::Mathematics and natural science: 400::Mathematics: 410::Statistics: 412 Integrated nested Laplace approximations applied statistics Latent Gaussian models MAT-3907 |
description |
This thesis uses data from the Tromsø Study and weather data from the Norwegian Meteorological Institute to study the mortality hazard rate and incidence rate of myocardial infarction (MI) in Tromsø using a latent Gaussian modelling framework. Inference is performed using integrated nested Laplace approximations (INLA). This thesis presents the datasets and describes the modelling and computational framework, before analysis is performed. To study the mortality hazard rate after MI, a Cox proportional hazards model has been implemented. A model without a seasonal effect with sex as a stratum variable was deemed the best fit. The results show an increased risk in the month after a MI. After the first month, the risk drops, before it increases with age. The mortality hazard rate is slightly higher for men than for women. To study the change in the rate of MI during the time of the study, a Bayesian age-period-cohort model has been implemented. The model only includes the men of the study. This model studies the rate of MI on three different time scales: age, period, and cohort. The effects from age, period, and cohort are not directly identifiable. However, second differences describing the curvature and relative risk ratios are identifiable, as is the overall rate. The results show the incidence rate of MI decreasing with period, and increasing with age. |
format |
Master Thesis |
author |
Skjold, Gunnhild |
author_facet |
Skjold, Gunnhild |
author_sort |
Skjold, Gunnhild |
title |
A study of the incidence and mortality hazard rate of myocardial infarction in Tromsø |
title_short |
A study of the incidence and mortality hazard rate of myocardial infarction in Tromsø |
title_full |
A study of the incidence and mortality hazard rate of myocardial infarction in Tromsø |
title_fullStr |
A study of the incidence and mortality hazard rate of myocardial infarction in Tromsø |
title_full_unstemmed |
A study of the incidence and mortality hazard rate of myocardial infarction in Tromsø |
title_sort |
study of the incidence and mortality hazard rate of myocardial infarction in tromsø |
publisher |
UiT Norges arktiske universitet |
publishDate |
2019 |
url |
https://hdl.handle.net/10037/16090 |
long_lat |
ENVELOPE(141.467,141.467,-66.782,-66.782) |
geographic |
Laplace Tromsø |
geographic_facet |
Laplace Tromsø |
genre |
Tromsø |
genre_facet |
Tromsø |
op_relation |
https://hdl.handle.net/10037/16090 |
op_rights |
openAccess Copyright 2019 The Author(s) |
_version_ |
1766219032772476928 |