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Rubayyat Hashmi

Bio: Rubayyat Hashmi is an academic researcher from University of Southern Queensland. The author has contributed to research in topics: Medicine & Mental health. The author has an hindex of 5, co-authored 10 publications receiving 186 citations. Previous affiliations of Rubayyat Hashmi include American International University-Bangladesh.

Papers
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Journal ArticleDOI
TL;DR: In this article, the authors examined the effects of environmental regulation and innovation on the carbon emission reduction of OECD countries during the period 1999-2014 and developed a new model called "stochastic impacts by regression on population, affluence, regulation and technology" (STIRPART) to extend the analysis on the evaluation of factors influencing carbon emissions.

396 citations

Journal ArticleDOI
01 Nov 2020-Heliyon
TL;DR: There is a negative impact of public sector governance and religiosity on tax evasion, which implies that the higher the degree of economic freedoms, the lower the tax evasion.

19 citations

Journal ArticleDOI
TL;DR: In this article, the authors explored the most recent national prevalence and trends of adult overweight and obesity in Australia and investigated geographic remoteness as a potential risk factor for an individual being overweight or obese in adulthood.
Abstract: The prevalence of overweight and obesity has been increasing globally and has become a significant public health concern in Australia in the two past decades. This study explores the most recent national prevalence and trends of adult overweight and obesity in Australia. It will also investigate geographic remoteness as a potential risk factor for an individual being overweight or obese in adulthood. A retrospective longitudinal study that utilised 14 successive waves (wave 6 through 19) of a nationally representative linked individual-level survey. Data was obtained from the Household, Income and Labour Dynamics in Australia survey. The data on 199,675 observations from 26,713 individuals aged ≥ 15 years over the period 2006 to 2019 was analysed. Random-effects logit model was employed to estimate the association between geographic remoteness and the risk of excessive weight gain. The results reveal that the prevalence of overweight, obesity and combined overweight and obesity among Australian adults in 2019 were 34%, 26% and 60%, respectively. The analysis shows that the prevalence of overweight and obesity varies by geographic remoteness. Adults from regional city urban (OR 1.53, 95% CI 1.16–2.03) and rural areas (OR 1.32, 95% CI 1.18–1.47) were more likely to be obese compared with their counterparts from major city urban areas. The results also show that adults living in major city urban areas, regional city urban areas, and regional city rural areas in Australia were 1.53 (OR 1.53, 95% CI 1.16–2.03), 1.32 (OR 1.32, 95% CI 1.18–1.47), and 1.18 (OR 1.18, 95% CI 1.08–1.29) times more likely to be overweight compared with their counterparts from major city urban areas in Australia. Substantial geographic variation in the prevalence of overweight and obesity exists among Australian adults and appears to be increasing. Public health measures should focus on contextual obesogenic factors and behavioural characteristics to curb the rising prevalence of adult obesity.

16 citations

Journal ArticleDOI
16 Nov 2021-PLOS ONE
TL;DR: In this article, the authors investigated whether obesity is a significant risk factor for type 2 diabetes, heart diseases, asthma, arthritis, and depression in Australian middle-aged and older adults.
Abstract: Background Overweight and obesity impose a significant health burden in Australia, predominantly the middle-aged and older adults. Studies of the association between obesity and chronic diseases are primarily based on cross-sectional data, which is insufficient to deduce a temporal relationship. Using nationally representative panel data, this study aims to investigate whether obesity is a significant risk factor for type 2 diabetes, heart diseases, asthma, arthritis, and depression in Australian middle-aged and older adults. Methods Longitudinal data comprising three waves (waves 9, 13 and 17) of the Household, Income and Labour Dynamics in Australia (HILDA) survey were used in this study. This study fitted longitudinal random-effect logistic regression models to estimate the between-person differences in the association between obesity and chronic diseases. Results The findings indicated that obesity was associated with a higher prevalence of chronic diseases among Australian middle-aged and older adults. Obese adults (Body Mass Index [BMI] ≥ 30) were at 12.76, 2.05, 1.97, 2.25, and 1.96, times of higher risks of having type 2 diabetes (OR: 12.76, CI 95%: 8.88–18.36), heart disease (OR: 2.05, CI 95%: 1.54–2.74), asthma (OR: 1.97, CI 95%: 1.49–2.62), arthritis (OR: 2.25, 95% CI: 1.90–2.68) and depression (OR: 1.96, CI 95%: 1.56–2.48), respectively, compared with healthy weight counterparts. However, the study did not find any evidence of a statistically significant association between obesity and cancer. Besides, gender stratified regression results showed that obesity is associated with a higher likelihood of asthma (OR: 2.64, 95% CI: 1.84–3.80) among female adults, but not in the case of male adults. Conclusion Excessive weight is strongly associated with a higher incidence of chronic disease in Australian middle-aged and older adults. This finding has clear public health implications. Health promotion programs and strategies would be helpful to meet the challenge of excessive weight gain and thus contribute to the prevention of chronic diseases.

15 citations

Journal ArticleDOI
TL;DR: The results suggest that exposure to just one life shock will result in a greater risk of mental disorder in the most disadvantaged socioeconomic groups and policies aimed at reducing socioeconomic inequality in mental health should account for these shocks when designing interventions.

14 citations


Cited by
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01 Jan 2016
TL;DR: The multivariate data analysis with readings is universally compatible with any devices to read and is available in the book collection an online access to it is set as public so you can download it instantly.
Abstract: Thank you very much for reading multivariate data analysis with readings. As you may know, people have look hundreds times for their favorite books like this multivariate data analysis with readings, but end up in malicious downloads. Rather than reading a good book with a cup of coffee in the afternoon, instead they are facing with some infectious virus inside their desktop computer. multivariate data analysis with readings is available in our book collection an online access to it is set as public so you can download it instantly. Our books collection saves in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the multivariate data analysis with readings is universally compatible with any devices to read.

1,163 citations

Posted Content
TL;DR: In this paper, the authors focus on three environmental impacts particularly influenced by population age-structure, including carbon emissions from transport and residential energy and electricity consumption, as well as aggregate carbon emissions for a panel of developed countries, and take as their starting point the STIRPAT framework.
Abstract: We focus on three environmental impacts particularly influenced by population age-structure—carbon emissions from transport and residential energy and electricity consumption—as well as aggregate carbon emissions for a panel of developed countries, and take as our starting point the STIRPAT framework. Among our contributions is to further disaggregate population into three particularly key age groups: 20-34, 35-49, and 50-64, and by doing so demonstrate that population’s environmental impact differs considerably across age-groups, with the older age-groups (ones typically associated with larger households) actually exerting a negative influence. Furthermore, those age-specific population influences are different (in absolute and relative terms) for the different environmental impacts we analyze. Also, we find that urbanization, in developed countries, best measures access to a country’s power grid, and thus, is positively associated with energy consumption in the residential sector. Lastly, we suggest some modelling and methodological improvements to the STIRPAT framework.

388 citations

Journal ArticleDOI
TL;DR: Empirical results show that the EKC hypothesis is not valid, and energy intensity and energy structure are important determinants of environmental degradation, and possible policy suggestions are discussed in the present study.

277 citations

Journal ArticleDOI
TL;DR: In this paper, the effects of financial globalization, urbanization, eco-innovation, and economic growth on the ecological footprints of the G7 countries using annual frequency data spanning from 1980 to 2016, several latest econometric methods, that are robust to handling cross-sectionally dependent panel datasets, are employed to ascertain the environmental impacts of these variables.

246 citations

Journal ArticleDOI
TL;DR: The results find that the eleventh FYP environmental regulation negatively influences enterprise green innovation efficiency in a short-term through reducing cash flows, and suggests that the government should consider the effect of CCR on economy and focus on the heterogeneity of enterprises during designing environmental policies.

199 citations