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Article ; Online: Prevalence and Risk Factors of Musculoskeletal Pain among Construction Industry Workers in a Low-Income Country

Natasha Shaukat / Zafar Fatmi

Iranian Journal of Health, Safety and Environment, Vol 7, Iss 3, Pp 1501-

2022 Volume 1508

Abstract: Musculoskeletal pain (MSP) is one of the major causes of disability around the world. We ought to determine the prevalence and risk factors of MSP among construction workers in Karachi, Pakistan. We carried out a cross-sectional study among 321 ... ...

Abstract	Musculoskeletal pain (MSP) is one of the major causes of disability around the world. We ought to determine the prevalence and risk factors of MSP among construction workers in Karachi, Pakistan. We carried out a cross-sectional study among 321 construction workers from five registered construction companies in Karachi, Pakistan. We administered an Extended Nordic Musculoskeletal Questionnaire (NMQ-E) to determine the frequency of MSP and inquired about socio-demographic characteristics, occupational and ergonomic risk factors, knowledge and practices regarding MSP. Age-adjusted logistic regression analysis was carried out to identify factors that were associated with MSP. The mean age of participants was 29.6 (±10.6) years. Low back pain was the most common (27.8%) complaint. The MSP risk was higher in the poorest strata [OR= 1.85, 95% CI:1.10-3.12], and those exposed to vibrations [OR=1.63, 95%CI: 1.05-2.54] during their work activities. Moreover, the unmarried [OR= 0.56, 95%CI: 0.35-0.91] and the workers of Punjabi ethnicity [OR=0.46, 95% CI: 0.27-0.76] were at a lower risk of MSP compared to married men and Sindhi workers. Of the 319 workers, the majority [202 (62.9%)] had low knowledge about occupational hazards, and [194 (60.4%)] health hazards, [131(40.8%)] MSP prevention strategies. More than one third [124(38.6)] workers, were not using personal protective equipment (PPEs) during work. The construction workers in Pakistan suffer from a very high prevalence of MSP. The study reports MSP from five major registered construction companies in Pakistan. The young group of workers reported difficulty working due to MSP. There is a dire need to design contextualized occupational health and safety policies and interventions with a focus on workers at higher risk of MSP.
Keywords	musculoskeletal pain ; ergonomics ; construction industry ; prevalence ; developing country ; Public aspects of medicine ; RA1-1270
Subject code	360 ; 690
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	Iranian Journal of Health, Safety and Environment
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Effect Of Cotton Dust Exposure On Respiratory Health Outcomes Among Textile Workers.

Sadia, Afreen / Ali, Yousaf / Tahir, Hasan Nawaz / Shaukat, Natasha / Irfan, Muhammad / Nafees, Asaad Ahmad

Journal of Ayub Medical College, Abbottabad : JAMC

2023 Volume 35, Issue 1, Page(s) 104–109

Abstract: Background: Cotton dust is generated during various textile manufacturing processes. Only a few studies from Pakistan assessed cotton dust exposure and explored the relationship of duration of work in the textile industry with respiratory health ... ...

Abstract	Background: Cotton dust is generated during various textile manufacturing processes. Only a few studies from Pakistan assessed cotton dust exposure and explored the relationship of duration of work in the textile industry with respiratory health outcomes. We aimed to assess cotton dust exposure and its association with lung function and respiratory symptoms among textile workers in Pakistan. Methods: We report findings from the baseline survey of the larger study, MultiTex, among 498 adult male textile workers from six mills conducted between October 2015-March 2016 in Karachi, Pakistan. Data collection included the use of standardized questionnaires; spirometry, and area dust measurements through UCB-PATS. Multivariable logistic and linear regression models were developed to assess the association of risk factors with respiratory symptoms and illnesses. Results: We found the mean age of workers to be 32.5 (±10) years; around 25% were illiterate. The prevalence of COPD, asthma, and byssinosis was 10%, 17%, and 2%, respectively. The median cotton dust exposure was 0.33 mg/m3 (IQR: 0.12-0.76). Increased duration of work among non-smokers was associated with a decline in lung function, FVC (-245 ml; 95% CI: -385.71, -104.89) and FEV1 (-200 ml; 95% CI: -328.71, -841.1). Workers with certain job titles (machine operators, helpers, and jobbers), those with greater duration of work, and higher dust exposure, were more likely to report respiratory symptoms and illnesses. Conclusions: We report a high prevalence of asthma and COPD and a low prevalence of byssinosis. Cotton dust exposure and duration of employment were associated with respiratory health outcomes. Our findings highlight the need for preventive interventions in the textile industry in Pakistan.
MeSH term(s)	Adult ; Male ; Humans ; Young Adult ; Dust ; Byssinosis/epidemiology ; Byssinosis/etiology ; Textiles ; Asthma ; Outcome Assessment, Health Care ; Pulmonary Disease, Chronic Obstructive
Chemical Substances	Dust
Language	English
Publishing date	2023-02-27
Publishing country	Pakistan
Document type	Journal Article
ZDB-ID	2192473-9
ISSN	1819-2718 ; 1025-9589
ISSN (online)	1819-2718
ISSN	1025-9589
DOI	10.55519/JAMC-01-10901
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Article: Exploring the Long-Term Disability Outcomes in Trauma Patients: Study Protocol.

Shaukat, Natasha / Merchant, Asma Altaf Hussain / Sahibjan, Fazila / Abbasi, Ayesha / Jarrar, Zeerak / Ahmed, Tanweer / Atiq, Huba / Khan, Uzma Rahim / Khan, NadeemUllah / Mushtaq, Saima / Rasul, Shahid / Hyder, Adnan / Razzak, Junaid / Haider, Adil

Research square

2024

Abstract: ... ...

Abstract	Objectives
Language	English
Publishing date	2024-04-10
Publishing country	United States
Document type	Preprint
DOI	10.21203/rs.3.rs-4238506/v1
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Article ; Online: Classification and Segmentation of Diabetic Retinopathy

Natasha Shaukat / Javeria Amin / Muhammad Imran Sharif / Muhammad Irfan Sharif / Seifedine Kadry / Lukas Sevcik

Applied Sciences, Vol 13, Iss 3108, p

A Systemic Review

2023 Volume 3108

Abstract: Diabetic retinopathy (DR) is a major reason of blindness around the world. The ophthalmologist manually analyzes the morphological alterations in veins of retina, and lesions in fundus images that is a time-taking, costly, and challenging procedure. It ... ...

Abstract	Diabetic retinopathy (DR) is a major reason of blindness around the world. The ophthalmologist manually analyzes the morphological alterations in veins of retina, and lesions in fundus images that is a time-taking, costly, and challenging procedure. It can be made easier with the assistance of computer aided diagnostic system (CADs) that are utilized for the diagnosis of DR lesions. Artificial intelligence (AI) based machine/deep learning methods performs vital role to increase the performance of the detection process, especially in the context of analyzing medical fundus images. In this paper, several current approaches of preprocessing, segmentation, feature extraction/selection, and classification are discussed for the detection of DR lesions. This survey paper also includes a detailed description of DR datasets that are accessible by the researcher for the identification of DR lesions. The existing methods limitations and challenges are also addressed, which will assist invoice researchers to start their work in this domain.
Keywords	diabetic retinopathy ; classification ; segmentation ; machine learning ; review ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
Subject code	006
Language	English
Publishing date	2023-02-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Three-Dimensional Semantic Segmentation of Diabetic Retinopathy Lesions and Grading Using Transfer Learning.

Shaukat, Natasha / Amin, Javeria / Sharif, Muhammad / Azam, Faisal / Kadry, Seifedine / Krishnamoorthy, Sujatha

Journal of personalized medicine

2022 Volume 12, Issue 9

Abstract: Diabetic retinopathy (DR) is a drastic disease. DR embarks on vision impairment when it is left undetected. In this article, learning-based techniques are presented for the segmentation and classification of DR lesions. The pre-trained Xception model is ... ...

Abstract	Diabetic retinopathy (DR) is a drastic disease. DR embarks on vision impairment when it is left undetected. In this article, learning-based techniques are presented for the segmentation and classification of DR lesions. The pre-trained Xception model is utilized for deep feature extraction in the segmentation phase. The extracted features are fed to Deeplabv3 for semantic segmentation. For the training of the segmentation model, an experiment is performed for the selection of the optimal hyperparameters that provided effective segmentation results in the testing phase. The multi-classification model is developed for feature extraction using the fully connected (FC) MatMul layer of efficient-net-b0 and pool-10 of the squeeze-net. The extracted features from both models are fused serially, having the dimension of N × 2020, amidst the best N × 1032 features chosen by applying the marine predictor algorithm (MPA). The multi-classification of the DR lesions into grades 0, 1, 2, and 3 is performed using neural network and KNN classifiers. The proposed method performance is validated on open access datasets such as DIARETDB1, e-ophtha-EX, IDRiD, and Messidor. The obtained results are better compared to those of the latest published works.
Language	English
Publishing date	2022-09-05
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2662248-8
ISSN	2075-4426
ISSN	2075-4426
DOI	10.3390/jpm12091454
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Article: Physical and mental health impacts of COVID-19 on healthcare workers: a scoping review.

Shaukat, Natasha / Ali, Daniyal Mansoor / Razzak, Junaid

International journal of emergency medicine

2020 Volume 13, Issue 1, Page(s) 40

Abstract: Background: Coronavirus disease (COVID-19) pandemic has spread to 198 countries, with approximately 2.4 million confirmed cases and 150,000 deaths globally as of April 18. Frontline healthcare workers (HCWs) face a substantially higher risk of infection ...

Abstract	Background: Coronavirus disease (COVID-19) pandemic has spread to 198 countries, with approximately 2.4 million confirmed cases and 150,000 deaths globally as of April 18. Frontline healthcare workers (HCWs) face a substantially higher risk of infection and death due to excessive COVID-19 exposure. This review aimed at summarizing the evidence of the physical and mental health impacts of COVID-19 pandemic on health-care workers (HCWs). Methods: We used the Arksey O'Malley framework to conduct a scoping review. A systematic literature search was conducted using two databases: PubMed and Google Scholar. We found 154 studies, and out of which 10 met our criteria. We collected information on the date of publication, first author's country, the title of the article, study design, study population, intervention and outcome, and key findings, and divided all research articles into two domains: physical and mental health impact. Results: We reviewed a total of 154 articles from PubMed (126) and Google Scholar (28), of which 58 were found to be duplicate articles and were excluded. Of the remaining 96 articles, 82 were excluded after screening for eligibility, and 4 articles did not have available full texts. Ten full-text articles were reviewed and included in this study. Our findings identified the following risk factors for COVID-19-related health impact: working in a high-risk department, diagnosed family member, inadequate hand hygiene, suboptimal hand hygiene before and after contact with patients, improper PPE use, close contact with patients (≥ 12 times/day), long daily contact hours (≥ 15 h), and unprotected exposure. The most common symptoms identified amongst HCWs were fever (85%), cough (70%), and weakness (70%). Prolonged PPE usage led to cutaneous manifestations and skin damage (97%), with the nasal bridge (83%) most commonly affected site. HCWs experienced high levels of depression, anxiety, insomnia, and distress. Female HCWs and nurses were disproportionately affected. Conclusion: The frontline healthcare workers are at risk of physical and mental consequences directly as the result of providing care to patients with COVID-19. Even though there are few intervention studies, early data suggest implementation strategies to reduce the chances of infections, shorter shift lengths, and mechanisms for mental health support could reduce the morbidity and mortality amongst HCWs.
Keywords	covid19
Language	English
Publishing date	2020-07-20
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	2411462-5
ISSN	1865-1380 ; 1865-1372
ISSN (online)	1865-1380
ISSN	1865-1372
DOI	10.1186/s12245-020-00299-5
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Article ; Online: Assessing the Feasibility of a Multifaceted Intervention Package for Improving Respiratory Health of Textile Workers: Findings From the MultiTex Pilot Study in Karachi, Pakistan.

Nafees, Asaad Ahmed / Ali, Yousaf / Sadia, Afreen / Shaukat, Natasha / Irfan, Muhammad / Fatmi, Zafar / Azam, Iqbal / Matteis, Sara De / Burney, Peter / Cullinan, Paul

Asia-Pacific journal of public health

2024 Volume 36, Issue 2-3, Page(s) 202–209

Abstract: We piloted the development and implementation of a multifaceted intervention package for improving respiratory health among textile workers using a pre-post design at six mills in Karachi. The intervention, implemented following a baseline survey (n = ... ...

Abstract	We piloted the development and implementation of a multifaceted intervention package for improving respiratory health among textile workers using a pre-post design at six mills in Karachi. The intervention, implemented following a baseline survey (n = 498), included health and safety training of workers and managers, promotion of cotton dust control measures, and the provision of facemasks. Follow-up surveys were conducted at 1, 6, and 12 months post-intervention. Knowledge, attitude, and practice (KAP) scores and respiratory symptoms were assessed through a questionnaire and spirometry was conducted. The intervention was provided to 230 workers and led to an improvement in KAP scores that was more likely among workers with a higher educational status, spinners, smokers, those with a permanent employment status, working in morning shifts, and with ⩾5 years of textile experience. We found the intervention acceptable and feasible in these textile mills henceforth, trials are required to determine its effectiveness.
MeSH term(s)	Humans ; Pilot Projects ; Pakistan ; Feasibility Studies ; Textiles ; Spirometry ; Dust/prevention & control ; Dust/analysis ; Occupational Exposure ; Textile Industry
Chemical Substances	Dust
Language	English
Publishing date	2024-01-21
Publishing country	China
Document type	Journal Article
ZDB-ID	1025444-4
ISSN	1941-2479 ; 1010-5395
ISSN (online)	1941-2479
ISSN	1010-5395
DOI	10.1177/10105395231226273
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Article ; Online: Physical and mental health impacts of COVID-19 on healthcare workers

Shaukat, Natasha / Ali, Daniyal Mansoor / Razzak, Junaid

International Journal of Emergency Medicine

a scoping review

2020 Volume 13, Issue 1

Keywords	Emergency Medicine ; covid19
Language	English
Publisher	Springer Science and Business Media LLC
Publishing country	us
Document type	Article ; Online
ZDB-ID	2411462-5
ISSN	1865-1380 ; 1865-1372
ISSN (online)	1865-1380
ISSN	1865-1372
DOI	10.1186/s12245-020-00299-5
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Article ; Online: Three-Dimensional Semantic Segmentation of Diabetic Retinopathy Lesions and Grading Using Transfer Learning

Natasha Shaukat / Javeria Amin / Muhammad Sharif / Faisal Azam / Seifedine Kadry / Sujatha Krishnamoorthy

Journal of Personalized Medicine, Vol 12, Iss 1454, p

2022 Volume 1454

Abstract	Diabetic retinopathy (DR) is a drastic disease. DR embarks on vision impairment when it is left undetected. In this article, learning-based techniques are presented for the segmentation and classification of DR lesions. The pre-trained Xception model is utilized for deep feature extraction in the segmentation phase. The extracted features are fed to Deeplabv3 for semantic segmentation. For the training of the segmentation model, an experiment is performed for the selection of the optimal hyperparameters that provided effective segmentation results in the testing phase. The multi-classification model is developed for feature extraction using the fully connected (FC) MatMul layer of efficient-net-b0 and pool-10 of the squeeze-net. The extracted features from both models are fused serially, having the dimension of N × 2020, amidst the best N × 1032 features chosen by applying the marine predictor algorithm (MPA). The multi-classification of the DR lesions into grades 0, 1, 2, and 3 is performed using neural network and KNN classifiers. The proposed method performance is validated on open access datasets such as DIARETDB1, e-ophtha-EX, IDRiD, and Messidor. The obtained results are better compared to those of the latest published works.
Keywords	deeplabv3 ; convolutional neural network ; Messidor ; lesions ; DR ; Medicine ; R
Subject code	006
Language	English
Publishing date	2022-09-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Physical and mental health impacts of COVID-19 on healthcare workers

Natasha Shaukat / Daniyal Mansoor Ali / Junaid Razzak

International Journal of Emergency Medicine, Vol 13, Iss 1, Pp 1-

a scoping review

2020 Volume 8

Abstract: Abstract Background Coronavirus disease (COVID-19) pandemic has spread to 198 countries, with approximately 2.4 million confirmed cases and 150,000 deaths globally as of April 18. Frontline healthcare workers (HCWs) face a substantially higher risk of ... ...

Abstract	Abstract Background Coronavirus disease (COVID-19) pandemic has spread to 198 countries, with approximately 2.4 million confirmed cases and 150,000 deaths globally as of April 18. Frontline healthcare workers (HCWs) face a substantially higher risk of infection and death due to excessive COVID-19 exposure. This review aimed at summarizing the evidence of the physical and mental health impacts of COVID-19 pandemic on health-care workers (HCWs). Methods We used the Arksey O’Malley framework to conduct a scoping review. A systematic literature search was conducted using two databases: PubMed and Google Scholar. We found 154 studies, and out of which 10 met our criteria. We collected information on the date of publication, first author’s country, the title of the article, study design, study population, intervention and outcome, and key findings, and divided all research articles into two domains: physical and mental health impact. Results We reviewed a total of 154 articles from PubMed (126) and Google Scholar (28), of which 58 were found to be duplicate articles and were excluded. Of the remaining 96 articles, 82 were excluded after screening for eligibility, and 4 articles did not have available full texts. Ten full-text articles were reviewed and included in this study. Our findings identified the following risk factors for COVID-19-related health impact: working in a high-risk department, diagnosed family member, inadequate hand hygiene, suboptimal hand hygiene before and after contact with patients, improper PPE use, close contact with patients (≥ 12 times/day), long daily contact hours (≥ 15 h), and unprotected exposure. The most common symptoms identified amongst HCWs were fever (85%), cough (70%), and weakness (70%). Prolonged PPE usage led to cutaneous manifestations and skin damage (97%), with the nasal bridge (83%) most commonly affected site. HCWs experienced high levels of depression, anxiety, insomnia, and distress. Female HCWs and nurses were disproportionately affected. Conclusion The frontline healthcare workers are at risk of physical and mental consequences directly as the result of providing care to patients with COVID-19. Even though there are few intervention studies, early data suggest implementation strategies to reduce the chances of infections, shorter shift lengths, and mechanisms for mental health support could reduce the morbidity and mortality amongst HCWs.
Keywords	COVID-19 ; Healthcare workers ; Health impacts ; Risk factors ; Occupational health ; Medical emergencies. Critical care. Intensive care. First aid ; RC86-88.9 ; covid19
Subject code	306
Language	English
Publishing date	2020-07-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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