ABSTRACT
BACKGROUND: Figures from Iranian cancer registries indicate that Isfahan ranks first in female breast cancer incidence. Although few previous studies have examined whether the breast cancer incidence trend in Isfahan province has increased over a given period of time, this study employed a joint point regression analysis to answer the same question. Moreover, it compared the data of Isfahan province, from a developing country, with those of England, as a representative of developed countries, and tried to explain the causes of the differences observed between the trends. METHODS: This repeated cross-sectional study was conducted on the data of 6057 women in Isfahan province and of 141,011 women in England with breast cancer over the years 2001-2013. The incidence rates were calculated using direct standardization method and based on the 2013 standard European population. For an analysis of the trends in breast cancer incidence rates, Joint Point Regression program, version 4.3.1.0, released in April 2016, was employed. RESULTS: The mean age-standardized incidence rate (ASR) was calculated to be 34.7 per100,000 population over the years 2001 to 2013, which indicated an increase from 22 to 68 in Isfahan province. The corresponding mean ASR for England has also risen from 147.5 to 170.1 per 100,000 women during the same time period. The average annual percentage changes (AAPCs) for Isfahan and England were also calculated to be 9.6 and 1.1, respectively. This indicated an increasing trend in breast cancer incidence rates for Isfahan province over the period in question. CONCLUSIONS: The drastic discrepancy in breast cancer incidence rates between these two regions may be attributed to differences in an improved cancer registry system in Iran and women's developing awareness of the cancer over time.
ABSTRACT
BACKGROUND: A comprehensive study on the interaction of cardiovascular disease (CVD) risk factors is critical to prevent cardiovascular events. The main focus of this study is thus to understand direct and indirect relationships between different CVD risk factors. METHODS: A longitudinal data on adults aged ≥35 years, who were free of CVD at baseline, were used in this study. The endpoints were CVD events, whereas their measurements were demographic, lifestyle components, socio-economics, anthropometric measures, laboratory findings, quality of life status, and psychological factors. A Bayesian structural equation modelling was used to determine the relationships among 21 relevant factors associated with total CVD, stroke, acute coronary syndrome (ACS), and fatal CVDs. RESULTS: In this study, a total of 3161 individuals with complete information were involved in the study. A total of 407 CVD events, with an average age of 54.77(10.66) years, occurred during follow-up. The causal associations between six latent variables were identified in the causal network for fatal and non-fatal CVDs. Lipid profile, with the coefficient of 0.26 (0.01), influenced the occurrence of CVD events as the most critical factor, while it was indirectly mediated through risky behaviours and comorbidities. Lipid profile at baseline was influenced by a wide range of other protective factors, such as quality of life and healthy lifestyle components. CONCLUSIONS: Analysing a causal network of risk factors revealed the flow of information in direct and indirect paths. It also determined predictors and demonstrated the utility of integrating multi-factor data in a complex framework to identify novel preventable pathways to reduce the risk of CVDs.
