ORCID Profile
0000-0001-5513-0337
Current Organisation
Sam Houston State University
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Publisher: MDPI AG
Date: 04-10-2019
Abstract: Coastal areas in South Asian countries are particularly vulnerable to elevated water salinity. Drinking water salinity has been found to be associated with cardiovascular diseases (CVD), diarrhea, and abdominal pain. Our study aimed to find if excess drinking water salinity was associated with increased hospital visits with an array of health effects in coastal sub-districts of Bangladesh. A cross-sectional study was conducted with 157 participants from three coastal sub-districts. A face-to-face interview was conducted to collect salinity exposure and hospital visit data. Water s les were collected from both drinking and other household water sources for the measurement of salinity and total dissolved solids (TDS). CVD, diarrhea, and abdominal pain related hospital visits were found to be significantly associated with high water salinity and TDS. Households exposed to high salinity demonstrated a higher frequency of hospital visits than the low salinity-exposed households. People exposed to high salinity seemed to lack awareness regarding salinity-inducing health effects. Water salinity is a public health concern that will continue to rise due to climate change. Therefore, raising awareness about the health risks of water salinity is essential for the government to frame policies and mitigation strategies to control this emerging threat.
Publisher: Informa UK Limited
Date: 25-11-2023
Publisher: Springer Science and Business Media LLC
Date: 22-11-2018
Publisher: Elsevier BV
Date: 03-2020
Publisher: MDPI AG
Date: 04-07-2020
Abstract: Microbial contamination of fruit juices has caused major outbreaks, leading to significant morbidity and mortality in developing countries. The inept hygiene and safety practices followed by the juice vendors are the leading risk factors of the microbial contamination of juices. In this pilot study, the five most crowded markets in urban Delhi, including Kamla Nagar, University of Delhi (north c us), Tilak Nagar, Chandni Chowk, and Rohini, were selected for a questionnaire survey on the fruit juice vendors and the s ling of water used for juice preparation as well as sugarcane, orange, and mix fruit juices collected from these markets for the enumeration of total bacterial count (TBC), Escherichia coli, Salmonella, and Vibrio. Antibiotic susceptibility tests were performed using icillin, cefotaxime, chlor henicol, ciprofloxacin, and imipenem. The results indicated that the majority of the vendors were not following hygiene and safety practices when compared with the recommended standard safety practices. The use of municipal water by 95% of vendors with high TBC counts might have been the major source of microbial contamination in all types of fruit juices. E. coli and Salmonella contaminations were high in sugarcane (2 × 105 colony forming units (CFU)/mL) and mix fruit (2.2 × 105 CFU/mL) juice s les, respectively. On the other hand, Vibrio was found to be absent in almost all juice s les except for orange juice. All strains were found to be susceptible to chlor henicol, but resistant to icillin and cefotaxime. Only a few strains were resistant to ciprofloxacin, and only E. coli strains were resistant to imipenem. Taken together, the overall microbiological standards of fruit juices served by street vendors were not within the acceptable limits, perhaps due to the poor quality of water used to prepare juices and poor hygiene and safety practices followed by the vendors. More importantly, the isolated microbes demonstrated resistance to icillin and cefotaxime, which may have pressing public health implications. Post hoc power analyses identified the minimum s le size required for 80% power.
Publisher: MDPI AG
Date: 04-09-2019
Abstract: Pesticide exposure is an important rural public health concern that is linked to a spectrum of health outcomes in farmers. However, little is known about these effects on residents living in close proximity to agricultural fields and who are not involved in regular farming. This paper compared the effects of residential proximity to farming lands on a number of neurological and mental health outcomes in adults. A cross-sectional study was performed on 57 adults involved in farming only occasionally in rural Matlab in Bangladesh. A health and demographic surveillance system (HDSS) and geocoding were used to define proximity to the agricultural field. Neurological health was measured using the trail making test, vibrotactile threshold measurement, and dominant ulnar nerve conduction velocity (NCV) litude. An adapted Center for Epidemiological Studies Depression scale (CES-D) questionnaire was used to evaluate mental health. Results indicated that respondents living near agricultural fields had significantly higher vibrotactile threshold in big toes (p 0.004) and needed a longer time to complete the trail making test (p 0.004) than those living far from fields after accounting for the covariates. Results of this pilot study suggest further investigations to establish the impact of pesticide exposure among occasional and non-farmers on neurological health outcomes.
Publisher: JMIR Publications Inc.
Date: 30-05-2023
DOI: 10.2196/45434
Abstract: Opioid use disorder (OUD) is an addiction crisis in the United States. As recent as 2019, more than 10 million people have misused or abused prescription opioids, making OUD one of the leading causes of accidental death in the United States. Workforces that are physically demanding and laborious in the transportation, construction and extraction, and health care industries are prime targets for OUD due to high-risk occupational activities. Because of this high prevalence of OUD among working populations in the United States, elevated workers’ compensation and health insurance costs, absenteeism, and declined productivity in workplaces have been reported. With the emergence of new smartphone technologies, health interventions can be widely used outside clinical settings via mobile health tools. The major objective of our pilot study was to develop a smartphone app that can track work-related risk factors leading to OUD with a specific focus on high-risk occupational groups. We used synthetic data analyzed by applying a machine learning algorithm to accomplish our objective. To make the OUD assessment process more convenient and to motivate potential patients with OUD, we developed a smartphone-based app through a step-by-step process. First, an extensive literature survey was conducted to list a set of critical risk assessment questions that can capture high-risk behaviors leading to OUD. Next, a review panel short-listed 15 questions after careful evaluation with specific emphasis on physically demanding workforces—9 questions had two, 5 questions had five, and 1 question had three response options. Instead of human participant data, synthetic data were used as user responses. Finally, an artificial intelligence algorithm, naive Bayes, was used to predict the OUD risk, trained with the synthetic data collected. The smartphone app we have developed is functional as tested with synthetic data. Using the naive Bayes algorithm on collected synthetic data, we successfully predicted the risk of OUD. This would eventually create a platform to test the functionality of the app further using human participant data. The use of mobile health techniques, such as our mobile app, is highly promising in predicting and offering mitigation plans for disease detection and prevention. Using a naive Bayes algorithm model along with a representational state transfer (REST) application programming interface and cloud-based data encryption storage, respondents can guarantee their privacy and accuracy in estimating their risk. Our app offers a tailored mitigation strategy for specific workforces (eg, transportation and health care workers) that are most impacted by OUD. Despite the limitations of the study, we have developed a robust methodology and believe that our app has the potential to help reduce the opioid crisis.
Publisher: MDPI AG
Date: 28-11-2021
Abstract: Diarrheal diseases and respiratory infections (RI) are two leading causes of childhood mortality in low and middle-income countries. Effective handwashing at critical time-points may mitigate these diseases. However, there is a lack of published data investigating this association in school-aged children in India. This study is part of a larger prospective handwashing intervention study in a low-income community in New Delhi, India examining the associations between handwashing behavior and diarrhea and RI in schoolchildren. This current study reports the findings of the baseline survey administered to 272 mother–child dyads. Children aged 8–12 years, and their mothers, were recruited from six schools. A baseline questionnaire was used to collect sociodemographic data, handwash behavior, and mother-reported recent diarrhea and RI incidence among the children. Handwashing before and after preparing food, after defecation, and after cleaning dishes significantly reduced the odds of diarrhea by over 70%, and of RI by over 56%. Using a clean cloth after handwashing lowered odds of diarrhea and RI by 72% and 63% respectively. Around 60% of the participants believed that handwashing could prevent diarrhea and RI in their children. There was a low prevalence of handwashing at critical time-points and a poor perception regarding handwashing benefits. To improve handwashing behavior, hygiene promotion programs need to understand what motivates and hinders handwashing in vulnerable populations.
Publisher: JMIR Publications Inc.
Date: 31-12-2022
Abstract: pioid use disorder (OUD) is an addiction crisis in the United States. As recent as 2019, more than 10 million people have misused or abused prescription opioids, making OUD one of the leading causes of accidental death in the United States. Workforces that are physically demanding and laborious in the transportation, construction and extraction, and health care industries are prime targets for OUD due to high-risk occupational activities. Because of this high prevalence of OUD among working populations in the United States, elevated workers’ compensation and health insurance costs, absenteeism, and declined productivity in workplaces have been reported. ith the emergence of new smartphone technologies, health interventions can be widely used outside clinical settings via mobile health tools. The major objective of our pilot study was to develop a smartphone app that can track work-related risk factors leading to OUD with a specific focus on high-risk occupational groups. We used synthetic data analyzed by applying a machine learning algorithm to accomplish our objective. o make the OUD assessment process more convenient and to motivate potential patients with OUD, we developed a smartphone-based app through a step-by-step process. First, an extensive literature survey was conducted to list a set of critical risk assessment questions that can capture high-risk behaviors leading to OUD. Next, a review panel short-listed 15 questions after careful evaluation with specific emphasis on physically demanding workforces—9 questions had two, 5 questions had five, and 1 question had three response options. Instead of human participant data, synthetic data were used as user responses. Finally, an artificial intelligence algorithm, naive Bayes, was used to predict the OUD risk, trained with the synthetic data collected. he smartphone app we have developed is functional as tested with synthetic data. Using the naive Bayes algorithm on collected synthetic data, we successfully predicted the risk of OUD. This would eventually create a platform to test the functionality of the app further using human participant data. he use of mobile health techniques, such as our mobile app, is highly promising in predicting and offering mitigation plans for disease detection and prevention. Using a naive Bayes algorithm model along with a representational state transfer (REST) application programming interface and cloud-based data encryption storage, respondents can guarantee their privacy and accuracy in estimating their risk. Our app offers a tailored mitigation strategy for specific workforces (eg, transportation and health care workers) that are most impacted by OUD. Despite the limitations of the study, we have developed a robust methodology and believe that our app has the potential to help reduce the opioid crisis.
Publisher: Elsevier BV
Date: 08-2019
Publisher: Elsevier BV
Date: 07-2021
DOI: 10.1016/J.NEURO.2021.04.005
Abstract: In developing countries, there is a need for low-cost neurobehavioral (NB) test batteries for vulnerable populations, particularly for children exposed to environmental neurotoxicants. The objective of the current study was to assess the feasibility and test-retest reliability of the Behavioral Assessment and Research System (BARS) in children from a rural community in Bangladesh. Fifty healthy adolescents living in the Health Effects of Arsenic Longitudinal Study (HEALS) area in Araihazar, Bangladesh completed all six tests from the BARS in two test sessions scheduled two weeks apart. The BARS tests evaluated NB functions such as motor coordination, attention, memory, and information processing speed. The reliability assessment, evaluated by test-retest correlations demonstrated moderate to strong correlations (i.e., correlation coefficients ranged from 0.43 to 0.85), which were statistically significant (p < 0.05). Paired t-tests for comparing the test and retest outcomes indicated significant improvement in NB performance, highlighting learning and practice effects. NB performance improved with increasing age in most cases. Adolescent boys performed better than the girls in Finger Tapping, Digit Span, and Simple Reaction Time, whereas the girls performed better in Continuous Performance and Symbol Digit tests. The reliability scores (Pearson's correlations 0.43-0.85) were consistent with other children studies in different cultural settings. The effects of age and sex on NB tests were also consistent with findings reported in other countries. Overall, the findings of the study support the feasibility of using this computer-based test system to assess vulnerability of brain health due to environmental exposures among rural Bangladeshi children.
Location: United States of America
Location: United States of America
Location: United States of America
No related grants have been discovered for Khalid Khan.