RESUMO
AIM:To compare the differences of ocular biometric parameters of age-related cataract between Tibetan and Han ethnic groups, and to analyze the distribution characteristics of ocular biometric parameters in Tibetan cataract patients.METHODS:Retrospective cohort study. A total of 661 patients(1 030 eyes)with age-related cataract confirmed in the hospital between January 2019 and December 2020 were enrolled. The parameters of axial length, anterior chamber depth, keratometry, corneal astigmatism and astigmatic axis were measured by IOL Master 500 in 483 cases(739 eyes)of Tibetan age-related cataract patients and 178 cases(291 eyes)of Han patients.RESULTS:The axial length, anterior chamber depth and corneal astigmatism of the Tibetan patients with age-related cataract were 23.33(22.81, 23.86)mm, 3.04(2.79, 3.30)mm and 0.73(0.47, 1.07)D. The mean keratometry was 43.89±1.35 D. The results indicated that Tibetan cataract patients had shorter axial lengths and smaller keratometry compared to Han patients(all P<0.05). Age in Tibetan patients was negatively correlated with axial length and anterior chamber depth, and positively correlated with keratometry(all P<0.05). Tibetan male patients had longer axial lengths, deeper anterior chambers, and flatter corneas compared to female patients(all P<0.05).CONCLUSION:There were differences in ocular biometric parameters between age-related cataract patients of Tibetan and Han ethnicities. The distribution of ocular biometric parameters in Tibetan cataract patients varied across different age groups and gender groups.
RESUMO
The working-age population is an essential driver of economic growth that facilitates industrial growth, trade, and urbanization, but its impression on environmental quality is under-researched. This study proposes a novel framework to estimate the impact of demographic structure, industrial growth, and urbanization on two indicators of the environment (CO2 & Ecological footprints) in seven South Asian countries (SAARC) over 1985-2016 employing "Stochastic Impact by Regression on Population, Affluence, and Technology (STIRPAT)" framework. The results showed the variables have "cross-sectional dependence" and panel heterogeneity. Similarly, the Pedroni, Kao & Westerlund tests indicated the cointegration relationship between the models' chosen variables. The long-run empirical estimates imply that the linear term of industrial growth is negative. The quadratic term is positive, thus supporting the U-shaped Kuznets phenomenon in the SAARC countries. Similarly, the working-age population (demographic structure), urbanization, and trade are detrimental environmental quality indicators. The causal linkages developed between the variables duly verified the causality between demographic structure, urbanization, and industrial growth with environmental degradation based on ecological footprints and CO2 emissions. These results for SAARC countries offer important policies for theorists, academicians, and practitioners.
