Natural disasters, climate change, and their impact on inclusive wealth in G20 countries

Fang, Jianchun; Lau, Chi Keung Marco; Lu, Zhou; Wu, Wanshan; Zhu, Lili

doi:10.1007/s11356-018-3634-2

Cited by 70 publications

(42 citation statements)

References 32 publications

(25 reference statements)

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“…Due to urbanization, environmental degradation, climate change and other factors, the frequency of natural disasters has increased dramatically in recent years [1]. Natural disasters not only cause economic loss, injuries and deaths [2], but also cause severe psychological distress and psychiatric disorders [3]. Major depressive disorder (MDD) is one of the most common psychiatric disorders in natural disaster-exposed populations [4], and MDD symptoms increase with time among natural disasterexposed individuals [5].…”

Section: Introductionmentioning

confidence: 99%

The factor structure of major depressive symptoms in a sample of Chinese earthquake survivors

Wang

Cao

et al. 2021

BMC Psychiatry

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Background Experiencing natural disasters is associated with common mental disorders including major depressive disorder (MDD). However, the latent structure of MDD is widely debated, and few studies tested the MDD factor structure in Chinese natural disaster survivors. Therefore, the aim of the current study was to evaluate the factorial validity of the Patient Health Questionnaire-9 (PHQ-9) for DSM-5 major depressive disorder (MDD) symptoms in Chinese earthquake survivors. Method Participants were 1058 Chinese earthquake survivors. Self-reported measures included the PHQ-9 and the Short-Form Health Survey (SF-36). Confirmatory factor analysis (CFA) and structural equation modelling (SEM) was used to examine the latent structure of MDD and the associations between latent factors of MDD and different domains of health-related quality of life (HRQoL), respectively. Results In the current sample, the model consisted of somatic and cognitive/affective (non-somatic) factors demonstrated significantly better fit than the other competing MDD models (χ2 = 173.89, df = 26, CFI = 0.986, TLI = 0.981, RMSEA = 0.073, BIC = 18,091.13). Further SEM analyses indicated that the non-somatic factor was significantly related to both physical (β = − 0.362, p < .01) and psychosocial HRQoL (β = − 0.773, p < .01), while the somatic factor was a uniquely predictor of physical HRQoL (β = − 0.336, p < .01). Furthermore, we found the somatic factor partially mediated the relationship between the cognitive/affective factor and physical HRQoL (all ps < .05). Conclusions The MDD symptoms was best captured by a two-factor model comprised of somatic and cognitive/affective factors in Chinese natural disaster survivors. The two MDD factors were differentially associated with physical and psychosocial HRQoL, and the cognitive/affective factor associated physical HRQoL partially through the somatic factor. The current findings increase our understanding of latent structure of MDD symptoms, and carry implications for assessment and intervention of post-disaster mental health problems.

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Section: Introductionmentioning

confidence: 99%

The factor structure of major depressive symptoms in a sample of Chinese earthquake survivors

Wang

Cao

et al. 2021

BMC Psychiatry

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“…According to the aforementioned criteria, only Model 2a yielded acceptable fit, while other models were rejected due to large RMSEA values. The Mplus DIFFTEST indicated that only Model 2a was superior to model 1 (△χ 2 (1) = 45.653, p < 0.001). In terms of comparisons of non-nested models, the BIC value for model 2a was lower than the other models, and all △BIC were lower than 6 except the △BIC between Model 2a and other models (△BIC = 39.536).…”

Section: Descriptive Statisticsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The underlying dimensions of major depressive symptoms in a sample of Chinese earthquake survivor

Bi¹,

Wang²,

Cao³

et al. 2020

Preprint

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Background: Experiencing natural disasters is associated with common mental disorders including major depressive disorder (MDD). However, the latent structure of MDD is widely debated, and few studies examined the structure of MDD in Chinese natural disaster survivors. Therefore, this study aimed to evaluate the factorial validity of the Patient Health Questionnaire-9 (PHQ-9) for DSM-5 major depressive disorder (MDD) symptoms in Chinese earthquake survivors.Method: Participants were 1058 Chinese earthquake survivors. Self-reported measures included the PHQ-9 and the Short-Form Health Survey (SF-36). Confirmatory factor analysis (CFA) and structural equation modelling (SEM) was used to examine the latent structure of MDD and the associations between latent factors of MDD and different aspects of health-related quality of life, respectively.Results: The model comprised of somatic and non-somatic factors demonstrated significantly better fit than the other competing MDD models in the current sample. Further structural equation modeling analyses indicated that the non-somatic factor was significantly associated with both physical and psychosocial health-related quality of life, while the somatic factor was a uniquely predictor of physical health-related quality of life. Furthermore, the somatic factor was found to partially mediate the relationship between the non-somatic factor and physical health-related quality of life.Conclusions: The MDD symptoms was best captured by a two-factor model comprised of somatic and non-somatic factors in Chinese natural disaster survivors. The two MDD factors were differentially associated with physical and psychosocial health-related quality of life, and the non-somatic factor associated physical health-related quality of life partially through the somatic factor. The current findings add to extant knowledge of latent structure of MDD symptoms, and carry implications for assessment and intervention of post-disaster mental health problems.

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“…However, due to complex atmospheric processes, quantitative rainfall forecasting is challenging [24]. Changes in rainfall patterns affect many sectors of a country such as agriculture, economy, and disaster management [15]. Based on this evidence, the researchers are more and more interested in rainfall forecasting and use deterministic solvers [3,26] and random programs to provide different accurate and reliable forecasts [10,14,19,20,22,25,32].…”

Section: Introductionmentioning

confidence: 99%

Rainfall trend analysis and weather forecast accuracy in selected parts of Khyber Pakhtunkhwa, Pakistan

et al. 2021

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Climate change is a multidimensional phenomenon, which has various effects on people's environmental and socioeconomic conditions. In the agricultural economy that is susceptible to natural changes, its impact is more profound. Therefore, climate change directly affects society in different ways, and society must pay a price. Climate change, especially the changes in annual temperature and rainfall, has attracted widespread attention worldwide. The variability of these factors or the magnitude of fluctuations varies according to location. Therefore, in the context of climate change, especially in countries dominated by rainfed agriculture, studying the trend of meteorological variables is essential to assess climate-induced variations and propose feasible adaptation approaches. Focusing on this fact is the main goal of this research study was to determine the rainfall trend and the accuracy of predicted temperature at three particular stations of Khyber Pakhtunkhwa (Kp) Province, Pakistan. For this purpose, rainfall and temperature data were provided by Pakistan Meteorological Department (PMD), Islamabad, for the period 1960–2020. Two types of nonparametric techniques, Sen’s slope estimate and the Mann–Kendall test, were applied to determine a trend in the average monthly and annual rainfall. The results of the annual rainfall trend analysis showed that Peshawar and Dera Ismail Khan stations showed a positive increasing trend, while the monthly rainfall trend showed a negative decreasing trend for all stations. The trend was statistically significant for Peshawar and Saidu Sharif stations. The accuracy of predicted and actual temperature and rainfall indicated that mostly over-forecast occurred at Saidu Sharif and Peshawar. Most of the precipitation and temperature records showed under forecast for Dera Ismail Khan, but some over-prediction has also occurred. Graphical abstract

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Natural disasters, climate change, and their impact on inclusive wealth in G20 countries

Cited by 70 publications

References 32 publications

The factor structure of major depressive symptoms in a sample of Chinese earthquake survivors

The factor structure of major depressive symptoms in a sample of Chinese earthquake survivors

The underlying dimensions of major depressive symptoms in a sample of Chinese earthquake survivor

Rainfall trend analysis and weather forecast accuracy in selected parts of Khyber Pakhtunkhwa, Pakistan

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