Hematological effects of benzene in the petroleum industry

Liao, Ying-Yu

doi:10.14419/ijh.v3i1.4339

Cited by 3 publications

(2 citation statements)

References 11 publications

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“…(19,24,27) No statistically signi cant difference observed in individuals who were exposed to benzene and non-exposed to benzene regarding Eosinophil counts and TWBCs count, as illustrated in Tables 4, 5. These ndings support previous studies (24,28) regarding increased TWBCs count and contrast with the previous studies (21,25,29) who mentioned decreases in TWBCs count in benzene exposed compared to unexposed controls, and the study (19) who reported increased Eosinophil counts. The difference between recent study results and those of the other studies could be due to the period of exposure to benzene, blood parameters measured, and study design.…”

Section: Categorysupporting

confidence: 90%

Haematological Changes in Benzene Exposed Workers in Sudan

Elkhalifa¹

2020

Preprint

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Background: Exposure to benzene leads to toxicity and influences bone marrow leads to cancer, anaemia, lymphoma, multiple myeloma, leukaemia, aplastic anaemia, and other types of cancer. The current study aims to report haematological changes in workers exposed to benzene exposure <1 ppm compared with the participants of non-exposed to benzene.Methods: Analytical cross-sectional study design applied at Kosti city, Sudan, during the year 2018. According to inclusion criteria, eighty-seven benzene stations workers chosen randomly to participate as a study group and another eighty-seven apparent healthy non-exposed to benzene, age matched, chosen as a comparative group. Blood samples (2.5ml) collected from all participants in EDTA anticoagulant containers for Complete Blood Cells analysis.Results: The means of the lymphocyte, RBCs count, and MCHC significantly increased in the benzene stations workers compared with the non-exposed group. The lymphocyte mean (44.61±8.41% vs, 29.19±3.98%; P<0.001), RBCs mean (5.30±0.75 ×1012 vs, 4.97±0.59 × 1012; P=0.002), and HCHC mean (32.67±2.12% vs, 31.71±1.37%; P<0.001). The means of PCV, Hb, MCH, MCV, PLTs count, Monocyte counts, and the Neutrophil counts significantly decreased in the exposed group. The PCV mean (43.83±2.47 l/l vs, 44.95±1.15 l/l; P<0.001), Hb mean (13.11±2.28 g/dl vs, 14.33±1.48 g/dl; P<0.001), MCH mean (26.35±2.01pg vs, 29.88±1.98pg; P<0.001), MCV mean (78.69±4.66 fl vs, 85.93±6.73 fl; P<0.001), PLTs mean (240.78±71.37×103/l vs, 262.54±70.77×103/l; P=0.046), Monocyte mean (4.44±2.39%vs. 5.64±1.92%; P=0.001), and Neutrophil mean (36.98±14.93% vs, 47.99±14.54%; P<0.001). The Eosinophil counts and TWBCs count showed no statistically significant difference between the two groups. Conclusion: The exposure to benzene has a significant haematological change in most of the complete blood count parameters among the benzene stations workers.

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Section: Categorysupporting

confidence: 90%

Haematological Changes in Benzene Exposed Workers in Sudan

Elkhalifa¹

2020

Preprint

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“…Negative values suggest that the mortality or EMS utilization is concentrated in poor regions while positive values suggest that the mortality or EMS utilization is concentrated in rich regions. A value of 0 means absolute equity among different regions [17]. …”

Section: Methodsmentioning

confidence: 99%

The equity of China’s emergency medical services from 2010–2014

Yan

Jiang

Qiu

et al. 2017

Int J Equity Health

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BackgroundWith the depth development of health care system reform in China, emergency medical services (EMS) is confronted with challenges as well as opportunities. This study aimed to analyze the equity of China’s EMS needs, utilization, and resources distribution, and put forward proposal to improve the equity.MethodThree emergency needs indicators (mortality rate of cardiovascular and cerebrovascular diseases, harm, and digestive system disease), two utilization indicators (emergency outpatient visits and rate of utilization) and one resource allocation indicator (number of EMS facilities) were collected after the review of the China Statistical Yearbook and the National Disease Surveillance System. Next, EMS related indicators were compared among 31 provinces from the eastern, central, and western regions of the country. Concentration Index (CI) were used to measure the equity of EMS needs and utilization among the western, central, and eastern regions. The Gini coefficient of demographic and geographic distribution of facilities represented the equity of resource allocation.ResultDuring 2010–2014, the CI of cardiovascular and cerebrovascular disease mortality changed from positive to negative, which indicates that the concentrated trend transferred from richer regions to the poorer area. Injury mortality (CI: range from − 0.1241to −0.1504) and digestive disease mortality (CI: range from − 0.1921 to − 0.2279) consistently concentrated in the poorer region, and the inequity among regions became more obviously year-by-year. The utilization of EMS (CI: range from 0.1074 to 0.0824) showed an improvement; however, the inequity reduced gradually. The EMS facilities distribution by population (Gini coefficient: range from 0.0922 to 0.1200) showed high equitability but the EMS facilities distribution by geography (Gini coefficient: range from 0.0922 to 0.1200) suggested a huge gap between regions because the Gini coefficients were greater than 0.5 in the past 5 years.ConclusionThere are some inequities of needs, utilization, and resource allocation in the China EMS. The government needs to stick to the principle of increasing investment in poorer regions, perfecting ambulance configuration and improving health workers’ professional skills to improve the equity and quality of EMS.

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