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1.
Cross-sectional personal network analysis of adult smoking in rural areas
Bianca-Elena Mihǎilǎ, Marian-Gabriel Hâncean, Matjaž Perc, Jürgen Lerner, Iulian Oană, Marius Geanta, José Luis Molina González, Cosmina Cioroboiu, 2024, izvirni znanstveni članek

Opis: Research on smoking behaviour has primarily focused on adolescents, with less attention given to middle-aged and older adults in rural settings. This study examines the influence of personal networks and sociodemographic factors on smoking behaviour in a rural Romanian community. We analysed data from 76 participants, collected through face-to-face interviews, including smoking status (non-smokers, current and former smokers), social ties and demographic details. Multilevel regression models were used to predict smoking status. The results indicate that social networks are essential in shaping smoking habits. Current smokers were more likely to have smoking family members, reinforcing smoking within familial networks, while non-smokers were typically embedded in non-smoking environments. Gender and age patterns show that women were less likely to smoke, and older adults were more likely to have quit smoking. These findings suggest that targeted interventions should focus not only on individuals but also on their social networks. In rural areas, family-based approaches may be particularly effective due to the strong influence of familial ties. Additionally, encouraging connections with non-smokers and former smokers could help disrupt smoking clusters, supporting smoking cessation efforts.
Ključne besede: network science, human behaviour, data science, smoking, social physics
Objavljeno v DKUM: 03.12.2024; Ogledov: 0; Prenosov: 0
.pdf Celotno besedilo (1,07 MB)
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2.
Modelling of the risk factors and chronic diseases that influence the development of serious health complications
Maja Atanasijević-Kunc, Jože Drinovec, Simona Ručigaj, Aleš Mrhar, 2008, izvirni znanstveni članek

Opis: Background: Some chronic diseases, like diabetes type 2 and hypertension, and risk factors, such as obesity, hypercholesterolemia, and smoking, are strongly correlated with the potential development of serious health complications that can threaten a patient's life or significantly influence the quality of life, while at the same time representing an enormous economic burden. Such complications include, for example, stroke, coronary heart disease, peripheralarterial vascular disease, end-stage renal disease and congestive heart failure. Methods: For a quantitative evaluation of the mentioned patient groups, the age distribution and an estimation of the treatment expenses a dynamic mathematical model was developed, where special attention was devoted to its structure, as it should enable the sequential construction and representation of different forms of data information. The model was realized in the Matlab program package with the Simulink Toolbox. Conclusions: A dynamic mathematical model is described that enables the observation of patients (in percentage terms) with diabetes type 2 and obesity, as well as those who smoke, have hypercholesterolemia and hypertension and all possible combinations of these problems, related to their age. Taking into account the Slovenian demographic data and annual treatment expenses, we were able to quantitatively evaluate these factors, not only in Slovenia but also in other developed regions where the demographic and economic situations are similar. It is also possible to extend the model to patients with serious complications, also taking into account the population dynamics, which is the goal of the next steps in our investigation. Regarding the presented results, it is estimated that from a group of a million people, those requiring treatment for diabetes type 2 cost as much as € 19.5 millions per year, since the treatment of one patient for one year is € 355. If all the sufferers requiring such treatment were located, as a consequence of more systematic medical examinations, an additional € 16 millions would be needed. In this group of one million people, as many as 40 % are expected to develop hypercholesterolemia, of which 26 % are diagnosed and treated adequately. The annual cost for the treatment of one patient is 313, which means that for a group of a million people the costs would be € 82 millions per year. An additional € 43.5 millions would be needed if all the sufferers with hypercholesterolemia were treated. Another chronic disease is hypertension. The annual cost for treating one patient is estimated to be € 271, and so for a group of a million people the treatment costs would be € 69.5 millions. If this were extended to include so far undiscovered sufferers with this chronic disease an additional € 14.5 millions would be needed.
Ključne besede: modelling, simulation, diabetes type 2, obesity, smoking, hypercholesterolemia, hypertension
Objavljeno v DKUM: 28.03.2017; Ogledov: 1144; Prenosov: 121
.pdf Celotno besedilo (1,10 MB)
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