Showing 3 results for Human Development Index
M Enayatrad, K Etemad, S Khodakarim, P Yavari,
Volume 13, Issue 3 (12-2017)
Abstract
Background and Objectives: Colorectal cancer is the fourth most common cancer and the fifth cause of cancer-related mortality in Iran. This study aimed to determine the incidence of colorectal cancer in men and women and to investigate its relationship with the human development index (HDI) and its components in Iranian provinces.
Methods: This ecological study was conducted to assess the correlation between age-specific incidence of colorectal cancer in men and women and the Human Development Index. We used the data of the Iranian Cancer Registry and Statistical Centre of Iran. We used a bivariate correlation method to assess the correlation of ASR and HDI. P values less than 0.05 were considered significant. All reported P-values are two-sided. Statistical analyses were performed using the SPSS software version 23.
Results: The highest incidence of colorectal cancer in men was seen in Tehran (78.16), Eastern Azerbaijan (41.14), and Semnan (62.13), and the highest incidence of colorectal cancer in women was seen in Tehran (47.18), Semnan (80.14), and Eastern Azerbaijan (82.12), respectively. The results showed that the incidence of colorectal cancer in men (r = 0.605) and women (r = 0.661) had a positive significant correlation with the Human Development Index (P<0.001).
Conclusion: The incidence of colorectal cancer was high in provinces with a higher human development index. Therefore, evaluation of the incidence of cancer by the Human Development Index and its components can be used to show a clearer picture of the distribution of cancer in each country and may be useful for cancer prevention plans.
Am Mosadeghrad, A Pour Reza , N Abolhasan Beigi Galezan , Sh Shahebrahimi,
Volume 14, Issue 4 (3-2019)
Abstract
Background and Objectives: Human Development Index (HDI) is an important indicator of a country’s development. On the other hand, mortality indicators are the most important indicators of the health of a society. This study aimed to examine the association between HDI and maternal, neonatal, infant, and under-five mortality rates in Iran between 2005 and 2016.
Methods: This longitudinal study was conducted using data collected from Iran Statistics Center, World Health Organization, and United Nations Development Program. SPSS software version 22 was used for data analysis. Pearson correlation test was applied to examine the correlation between HDI and mortality rates. Regression analysis was used to measure the effect of HDI on mortality rates.
Results: HDI increased from 0.690 in 2005 to 0.774 in 2016 (12% rise). Maternal, neonatal, infant, and under-five mortality rates decreased by 26, 41, 52, and 42% in 2016 compared to 2005, respectively. HDI had a significant indirect association with maternal (-0.973), neonatal (-0.983), infant (-0.739), and under-five mortality (-0.987). An increase of 0.01 in HDI reduced 1 maternal death per 100,000 births. An increase of 0.014, 0.009, and 0.008 in HDI decreased one neonatal, infant, and under-five death per 1000 births.
Conclusion: The results showed that increased HDI correlated with decreased mortality rates. Therefore, policy-makers should pay more attention to socio
M Hadian, M Tajvar, Ms Yekani Nejad , M Arab,
Volume 16, Issue 2 (8-2020)
Abstract
Background and Objectives: The main purpose of this study was to compare the predictive power of the Inequality-adjusted Human Development Index (IHDI) with the Human Development Index (HDI) with regard to the share of deaths caused by Non-Communicable Diseases (NCD) among all deaths in the world and Iran.
Methods: The data required for this cross-sectional ecological study were extracted from the reports of the United Nations Human Development Program and the WHO in 2015. Pearson correlation test was used to investigate the correlation of HDI and IHDI with the share of deaths caused by NCDs and linear regressions models were used to determine the associations of IHDI and HDI with the dependent variable.
Results: At a significant level of P<0.01, the dependent variable showed a strong positive correlation with HDI (0.892) and IHDI (0.899). Simple linear regression showed that HDI alone predicted the dependent variable well (Adj.R2=0.794, P<0.001).However, according to the multivariate linear regression model, when IHDI and HDI were included in the model, IHDI was able to predict the dependent variable well (Adj.R2=0.809, P=0.001), while the relationship between HDI and the dependent variable was no longer significant.
Conclusion: Although HDI alone is an important predictor of NCD status, it loses its influence in the presence of IHDI. Therefore, in addition to HDI, IHDI that illustrates the impact of inequality on human development can provide more information on the status of deaths caused by NCDs.
