Mediating factors explaining the associations between polycyclic aromatic hydrocarbons exposure, low socioeconomic status and diabetes: A structural equation modeling approach

Wang, Lu; Hou, Jian; Hu, Chen; Zhou, Yun; Sun, Huizhen; Zhang, Jiafei; Tian, Li; Gao, Erwei; Wang, Guiyang; Chen, Weihong; Yuan, Jing

doi:10.1016/j.scitotenv.2018.08.255

Cited by 28 publications

(7 citation statements)

References 40 publications

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“…In a cross-sectional study in China, serum PFOA and PFNA were significantly associated with BMI, with odds ratio (OR) of 12.1 (95% CI, 1.57–94.12) and 13.3 (95% CI, 2.38–74.38), respectively . These results indicated that exposure to some PFASs can be linked to higher BMI . In contrast, positive associations between FBG and PFHxS and also PFOS and PFOA concentrations were reported for the general population. ,, Unique and complex mixture exposure patterns in e-waste sites may explain the observed differences in associations between studies.…”

Section: Results and Discussionmentioning

confidence: 97%

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Health Status of Elderly People Living Near E-Waste Recycling Sites: Association of E-Waste Dismantling Activities with Legacy Perfluoroalkyl Substances (PFASs)

Zhang

Bai

et al. 2019

Environ. Sci. Technol. Lett.

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The elderly people living near electronic waste (e-waste) dismantling sites are susceptible to elevated chemical exposure, which is acerbated by hypometabolism and diminished immune tolerance. In this study, paired serum and urine samples collected from 1025 elderly people (≥60 years old) living near e-waste dismantling sites (n = 800) and reference areas (n = 225) in South China were analyzed for markers of health status and chemical exposures. Our results indicated that among all the health indicators fasting blood glucose (FBG) and urinary clinical markers were significantly higher in e-waste areas than in the reference area. Sixteen legacy perfluoroalkyl substances (PFASs) were determined in serum samples of elderly individuals living near e-waste dismantling areas (n = 171) and a reference area (n = 50). Serum PFASs concentrations in individuals from e-waste dismantling areas were significantly higher (p < 0.05) than those from the reference area, which indicated that e-waste dismantling activities are a source of exposure to PFASs. Association between PFASs exposure and personal health history showed that body mass index (BMI) was significantly positively (p < 0.05) associated with serum PFHxA, PFHpA, PFOA, and PFNA concentrations. Negative associations between FBG and serum PFUnDA (r = −0.160, p < 0.05) and PFTeDA (r = −0.157, p < 0.05) were also found. Our results suggest that PFASs exposure is associated with adverse health outcomes in elderly population living around e-waste dismantling sites.

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Section: Results and Discussionmentioning

confidence: 97%

“…For FBG, participants were grouped into three categories (hypoglycemia, <3.3 mmol/L; normal, 3.3–6.1 mmol/L; hyperglycemia, >6.1 mmol/L). According to the Working Group on Obesity in China, BMI was defined as normal-weight individuals (BMI < 24 kg/m 2 ), overweight (BMI = 24–28 kg/m 2 ), and obese (BMI ≥ 28 kg/m 2 ) …”

Section: Results and Discussionmentioning

confidence: 99%

Health Status of Elderly People Living Near E-Waste Recycling Sites: Association of E-Waste Dismantling Activities with Legacy Perfluoroalkyl Substances (PFASs)

Zhang

Bai

et al. 2019

Environ. Sci. Technol. Lett.

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“…Future studies should quantify the level of PAH exposure for direct comparison with existing evidence. Socioeconomic variables should be considered, as low socioeconomic status is associated with PAH exposure and development of T2DM [61]. Also, individual risk factors such as obesity, sleep, physical activity, nutrition, cigarette smoking, and alcohol drinking should be measured and considered when assessing the health effects of urinary PAH metabolites.…”

Section: Discussionmentioning

confidence: 99%

The Association between Urinary Polycyclic Aromatic Hydrocarbons Metabolites and Type 2 Diabetes Mellitus

Wang

2022

IJERPH

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Polycyclic aromatic hydrocarbons (PAHs) are considered to be endocrine disruptors. In this study, the evidence on the association between PAHs and diabetes was systematically reviewed. PubMed, EMBASE, and ISI Web of Science were systematically searched for studies reporting the association between PAHs and diabetes. Of the 698 articles identified through the search, nine cross-sectional studies were included. Seven were conducted in the general population and two in coke oven workers. Fixed-effects and random-effects models were used to calculate the total effect. Subgroup analysis was further carried out according to the types of PAH metabolites. The results showed that the odds of diabetes were significantly higher for the highest category of urinary naphthalene (NAP), fluorine (FLU), phenanthrene (PHEN), and total mono-hydroxylated (OH-PAH) metabolites compared to the lowest category. The pooled odds ratios (OR) and 95% confidence intervals (CI) were 1.52 (95%CI: 1.19, 1.94), 1.53 (95%CI: 1.36, 1.71), 1.43 (95%CI: 1.28, 1.60), and 1.49 (95%CI: 1.07, 2.08), respectively. In coke oven workers, 4-hydroxyphenanthrene (4-OHPh) was significantly correlated with an increased risk of diabetes. Exposure measurements, outcome definitions, and adjustment for confounders were heterogeneous between studies. The results of the current study demonstrate a potentially adverse effect of PAHs on diabetes. Further mechanistic studies and longitudinal studies are needed to confirm whether PAH metabolite levels are causative, and hence associative, with increased diabetes incidences.

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“…Structural Equation Modeling (SEM) is a multivariate analysis technique. It is used to estimate simultaneous multiple hypothesis relationships between latent variables (or underlying constructs) and observable variables 9 . This study used a cross-sectional design and structural equation modeling (SEM) to analyze the relationships between the variables 10 related to the patients with kidney stone disease.…”

Section: Structural Equation Modeling (Sem)mentioning

confidence: 99%

Assessment of the Prevalence of Kidney Stone Disease: A Structural Equation Model

Lokesh¹,

Alagirisamy²,

Manigandan³

et al. 2020

IJPHRD

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Background : This study entitled "Assessment of the Prevalence of Kidney Stone Disease: A Structural Equation Model" deals with the Kidney stones are of many types and have many causes, treatment depends on the size, nature and cause of the stone. Calcium and Oxalate stones are the most common varieties. Changes in the daily intake of Sodium, Protein, Calcium, Oxalate and fluid will slow stone formation. Dietary restrictions slow but do not cure kidney stones. Materials and Method :A retrospective cross-sectional study design was conducted. In this study, we have discussed the detection of kidney stones using structural equation modeling (SEM).Results : In general, structural equation models with scores for these measures of 0.9 or above are considered to have acceptable model fit and RMSEA is also a very popular measures this value is 0.19. This value indicates a not good model fit. Conclusion :There is strong evidence that there is no association between stone size, age, sex, height, BMI, and hydronephrosis.

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Mediating factors explaining the associations between polycyclic aromatic hydrocarbons exposure, low socioeconomic status and diabetes: A structural equation modeling approach

Cited by 28 publications

References 40 publications

Health Status of Elderly People Living Near E-Waste Recycling Sites: Association of E-Waste Dismantling Activities with Legacy Perfluoroalkyl Substances (PFASs)

Health Status of Elderly People Living Near E-Waste Recycling Sites: Association of E-Waste Dismantling Activities with Legacy Perfluoroalkyl Substances (PFASs)

The Association between Urinary Polycyclic Aromatic Hydrocarbons Metabolites and Type 2 Diabetes Mellitus

Assessment of the Prevalence of Kidney Stone Disease: A Structural Equation Model

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