Source apportionment of PM10 in Delhi, India using PCA/APCS, UNMIX and PMF

Jain, Srishti; Sharma, S.K.; Mandal, T. K.; Saxena, Mohit

doi:10.1016/j.partic.2017.05.009

“…Thus, identification and evaluation of these factors in combination with each other could, at least partly, open a clear window toward prediction of the CVD. To do so, PCA was employed as a powerful statistical tool to recognize potential contributors to the observed risk factors [16]. In consensus with the literature, our results showed that CRP, MCP-1, and insulin may be the key determinants of CVD predisposition, suggesting inflammation plays a key role in CVD development.…”

Section: Discussionsupporting

confidence: 71%

Principal Component Analysis of Adipocytokines and Insulin Associate with Risk Factors of Cardiovascular Diseases

Yarizadeh¹,

Setayesh

²

,

Askarpour

³

et al. 2020

Preprint

0

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Objectives : Obesity plays an important role in the development of chronic diseases like cardiovascular diseases and diabetes. The possible underlying mechanism for this connection is that adipose tissue secretes an array of chemical messenger adipokines proinflammatory cytokines (tumor necrosis factor-alpha, interleukin-6, and interleukin-1-beta). This study aimed to investigate the linkage between adipocytokines and insulin with the cardiovascular disease risk, with particular reference to the adipokines galectin-3, plasminogen activator inhibitor-1, interleukin-1-beta, C-reactive protein, and monocyte chemoattractant protein. Result: Two patterns were identified. The first pattern was galectin-3, plasminogen activator inhibitor-1 and interleukin-1-beta and the second one was C-reactive protein, insulin and monocyte chemoattractant protein-1. The second pattern was strongly associated with the higher scores for resting metabolic rate, diastolic blood pressure, homeostasis model insulin resistance index, lipid profile (except low density lipoprotein, total cholesterol), and body composition parameters (except fat free mass index and waist hip ratio), while negatively associated with age and high density lipoprotein level (all p < 0.05). The first pattern was, however, significantly associated with body fat mass, obesity degree percentage, waist circumference, fat mass index, and waist hip ratio (P < 0.05 for all).

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“…Thus, identification and evaluation of these factors in combination with each other could, at least partly, open a clear window toward prediction of the CVD. To do so, PCA was employed as a powerful statistical tool to recognize potential contributors to the observed risk factors [16]. Next, univariate regression performed to provide detailed information about quantitative associations between adipokines level and biological outcomes of the interest.…”

Section: Discussionmentioning

confidence: 99%

Principal component analysis of adipocytokines and insulin associate with risk factors of cardiovascular diseases

Yarizadeh

¹

,

Setayesh

²

,

Askarpoor

³

et al. 2020

View full text Add to dashboard Cite

Objectives: Obesity plays an important role in the development of chronic diseases like cardiovascular diseases and diabetes. The possible underlying mechanism for this connection is that adipose tissue secretes an array of chemical messenger adipokines proinflammatory cytokines (tumor necrosis factor-alpha, interleukin-6, and interleukin-1-beta). This study aimed to investigate the linkage between adipocytokines and insulin with the cardiovascular disease risk, with particular reference to the adipokines galectin-3, plasminogen activator inhibitor-1, and interleukin-1-beta, C-reactive protein, and monocyte chemoattractant protein. Result: Two patterns were identified. The first pattern was galectin-3, plasminogen activator inhibitor-1 and interleukin-1-beta and the second one was C-reactive protein, insulin and monocyte chemoattractant protein-1. The second pattern was strongly associated with the higher scores for resting metabolic rate, diastolic blood pressure, homeostasis model insulin resistance index, lipid profile (except low density lipoprotein, total cholesterol), and body composition parameters (except fat free mass index and waist hip ratio), while negatively associated with age and high density lipoprotein level (all p < 0.05). The first pattern was, however, significantly associated with body fat mass, obesity degree percentage, waist circumference, fat mass index, and waist hip ratio (p < 0.05 for all). This is a retrospective study. Ethics approval (IR.TUMS.VCR.REC.1395.1597).

show abstract

“…Thus, identification and evaluation of these factors in combination with each other could, at least partly, open a clear window toward prediction of the CVD. To do so, PCA was employed as a powerful statistical tool to recognize potential contributors to the observed risk factors [16].…”

Section: Discussionmentioning

confidence: 99%

Principal Component Analysis of Adipocytokines and Insulin Associate with Risk Factors of Cardiovascular Diseases

Yarizadeh¹,

Setayesh

²

,

Askarpour

³

et al. 2020

Preprint

View full text Add to dashboard Cite

Objectives : Obesity plays an important role in the development of chronic diseases like cardiovascular diseases and diabetes. The possible underlying mechanism for this connection is that adipose tissue secretes an array of chemical messenger adipokines proinflammatory cytokines (tumor necrosis factor-alpha, interleukin-6, and interleukin-1-beta). This study aimed to investigate the linkage between adipocytokines and insulin with the cardiovascular disease risk, with particular reference to the adipokines galectin-3, plasminogen activator inhibitor-1, interleukin-1-beta, C-reactive protein, and monocyte chemoattractant protein. Result: Two patterns were identified. The first pattern was galectin-3, plasminogen activator inhibitor-1 and interleukin-1-beta and the second one was C-reactive protein, insulin and monocyte chemoattractant protein-1. The second pattern was strongly associated with the higher scores for resting metabolic rate, diastolic blood pressure, homeostasis model insulin resistance index, lipid profile (except low density lipoprotein, total cholesterol), and body composition parameters (except fat free mass index and waist hip ratio), while negatively associated with age and high density lipoprotein level (all p < 0.05). The first pattern was, however, significantly associated with body fat mass, obesity degree percentage, waist circumference, fat mass index, and waist hip ratio (P < 0.05 for all).

show abstract

Source apportionment of PM10 in Delhi, India using PCA/APCS, UNMIX and PMF

Cited by 136 publications

References 107 publications

Principal Component Analysis of Adipocytokines and Insulin Associate with Risk Factors of Cardiovascular Diseases

Principal Component Analysis of Adipocytokines and Insulin Associate with Risk Factors of Cardiovascular Diseases

Principal component analysis of adipocytokines and insulin associate with risk factors of cardiovascular diseases

Principal Component Analysis of Adipocytokines and Insulin Associate with Risk Factors of Cardiovascular Diseases

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