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Fulltext Elucidating the Macroeconomic Determinants of Undernourishment in South Asian Countries: Building the Framework for Action

Aziz N, He J, Raza A, Sui H, Yue W

Front Public Health, 2021;9:696789.
PMID: 34458224 DOI: 10.3389/fpubh.2021.696789

Undernourishment is a big challenge for humanity across the world. Considering the significance of reducing undernourishment, the current study focuses on exploring the macroeconomic determinants of undernourishment in the South Asian panel. The study employed econometric models that are more robust to underpin cross-sectional dependency and heterogeneity in a panel data set. The overall findings reveal that an increase in food production increases undernourishment and infer that food availability at the national level is insufficient to reduce undernourishment unless poor people also had economic and physical access to food. In the case of economic growth and governance, the results are negatively significant in some countries. The results infer that GDP and quality of governance are nuanced in declining the rate of undernourishment in some countries, while in other countries where the results are found insignificant, the government should seek other interventions to curtail the prevalence of undernourishment. Unexpectedly, an increase in food prices lessens the undernourishment in developing countries that reflect that food prices might transform the dietary patterns of poor people from nutrient-rich foods to nutrient-poor staples, thus lead to undernourishment reduction but trigger overweight and obesity alongside. In conclusion, the results depict that policymakers should devise strategies keeping in view fundamental aspects of the country to reduce undernourishment.
Fulltext Comparative Studies on Patient Safety Culture to Strengthen Health Systems Among Southeast Asian Countries

Kang S, Ho TTT, Lee NJ

Front Public Health, 2020;8:600216.
PMID: 33511097 DOI: 10.3389/fpubh.2020.600216

Patient safety is an important issue in health systems worldwide. A systematic review of previous studies on patient safety culture in Southeast Asian countries is necessary for South Korea's partnership with these countries, especially given South Korea's assistance in strengthening the health systems of these developing countries. Studies on patient safety culture in Southeast Asian countries, published in English and Thai languages, were retrieved from computerized databases using keywords through a manual search. Data extraction, quality assessment, and analyses were performed using several tools. The review included 21 studies conducted in Indonesia (n = 8), Thailand (n = 5), Malaysia (n = 3), Vietnam (n = 2), Singapore (n = 1), and the Philippines (n = 1). They were analyzed and categorized into 12 dimensions of safety culture, and differences in response rate or scores were identified compared to the mean of the dimensions. The heterogeneous of safety culture's situation among Southeast Asian countries, both in practice and in research, can be explained since patient safety policy and its application are not prioritized as much as they are in developed countries in the priority compared to the developed countries. However, Vietnam, Cambodia, Myanmar, and Laos are the priority countries for South Korea's official healthcare development assistance in the Southeast Asia region. Vietnam, for instance, is an economically transitioning country; therefore, consolidated patient safety improvement by inducing patient safety culture in the provincial and central health system as well as strengthening project formulation to contribute to health policy formation are needed for sustainable development of the partner countries' health systems. It is recommended that more evidence-based proactive project planning and implementation be conducted to integrate patient safety culture into the health systems of developing countries, toward health policy on patient safety and quality service for the attainment of sustainable development goals in South Korea's development cooperation.
Fulltext Reliability and Accuracy of 2D Photogrammetry: A Comparison With Direct Measurement

Lim YC, Abdul Shakor AS, Shaharudin R

Front Public Health, 2021;9:813058.
PMID: 35155360 DOI: 10.3389/fpubh.2021.813058

Objective: Facial anthropometric data is important for the design of respirators. Two-dimensional (2D) photogrammetry has replaced direct anthropometric method, but the reliability and accuracy of 2D photogrammetry has not been quantified. This study aimed to assess inter-rater reliability of 2D photogrammetry and to examine the reliability and accuracy of 2D photogrammetry with direct measurement.
Design: A cross-sectional study.
Setting: Malaysia.
Participants: A subset of 96 participants aged 18 and above.
Primary and secondary outcomes: Ten facial dimensions were measured using direct measurement and 2D photogrammetry. An assessment of inter-rater reliability was performed using intra-class correlation (ICC) of the 2D images. In addition, ICC and Bland-Altman analyses were used to assess the reliability and agreement of 2D photogrammetry with direct measurement.
Results: Except for head breadth and bigonial breadth, which were also found to have low inter-rater reliability, there was no significant difference in the inter-rater mean value of the 2D photogrammetry. The mean measurements derived from direct measurement and 2D photogrammetry were mostly similar. However, statistical differences were noted for two facial dimensions, i.e., bizygomatic breadth and bigonial breadth, and clinically the magnitude of difference was also significant. There were no statistical differences in respect to the remaining eight facial dimensions, where the smallest mean difference was 0.3 mm and biggest mean difference was 1.0 mm. The ICC showed head breadth had poor reliability, whilst Bland-Altman analyses showed seven out of 10 facial dimensions using 2D photogrammetry were accurate, as compared to direct measurement.
Conclusion: Only certain facial measurements can be reliably and accurately measured using 2D photogrammetry, thus it is important to conduct a reliability and validation study before the use of any measurement methods in anthropometric studies. The results of this study also suggest that 2D photogrammetry can be used to supplement direct measurement for certain facial dimensions.
Fulltext "Suiting Up" to Enhance Empathy Toward Aging: A Randomized Controlled Study

Lee SWH, Teh PL

Front Public Health, 2020;8:376.
PMID: 32984232 DOI: 10.3389/fpubh.2020.00376

Background: Healthcare professionals who have a positive attitude and who are more empathetic toward older adults are in a better position to deliver quality healthcare. This study examines the impact of using an aging simulation suit on undergraduate pharmacy students' empathy levels.
Methods: One hundred and twenty first-year students enrolled in the Bachelor of Pharmacy course were randomized to either a medication review polypharmacy workshop (control) or an immersive aging simulation suit and medication review polypharmacy workshop (intervention). Intervention participants donned the aging suit and performed a series of tasks, including walking up a flight of stairs and filling up a form to simulate the physical limitations experienced by an older adult. The workshop was delivered at week 10 of semester. Both groups also completed a medication review polypharmacy workshop at week 12 of semester. The primary outcome was a measurement of change on the Jefferson Empathy Scale-Healthcare Professional Questionnaire among both groups at week 12 of semester. Secondary outcomes include the longitudinal impact of intervention after 3 months of the workshop and perceptions on learning.
Results: The use of a simulation suit did not increase participants' self-rated empathy compared to control. However, the suit enhanced the ability of participants to understand the physical limitations and visual issues associated with aging. Participants also felt that it enhanced their health advocacy, as it taught them the importance of listening, patience and respect for older adults.
Conclusion: The use of an immersive aging suit can be a useful adjunctive tool to help enhance students' understanding of the physical limitations and visual limitations of aging. Further research is needed to understand how these limitations affect other healthcare students. Trial Registration: ClinicalTrials.gov identifier: NCT04133727.
Study site: Monash University Malaysia
Fulltext Analysis of the Impact of External Debt on Health in an Emerging Asian Economy: Does FDI Matter?

Ma Y, Hu M, Zafar Q

Front Public Health, 2022;10:824073.
PMID: 35174125 DOI: 10.3389/fpubh.2022.824073

In this study, our main objective is to find the impact of FDI and external debt on health outcomes in emerging Asian economies from 1991 to 2019. To that end, we have collected data for seven economies: Bangladesh, Malaysia, Philippines, Thailand, Sri Lanka, China, and India. We have relied on the panel ARDL (PARDL) method for empirical analysis. The study's findings confirmed that the debt has increased infant mortality and decreased life expectancy in emerging Asian economies in the long run. On the other side, the FDI causes infant mortality to fall and life expectancy to rise in the long run in emerging Asian economies. Similarly, the health expenditures also reduced the infant mortality rate, though the impact is insignificant, and improved the life expectancy in emerging Asian economies. The causal analysis confirmed the two-way causality between health expenditure, infant mortality, and health expenditure and debt.
Fulltext Quality of life among health care workers in Arab countries 2 years after COVID-19 pandemic

Ghazy RM, Abubakar Fiidow O, Abdullah FSA, Elbarazi I, Ismail II, Alqutub ST, et al.

Front Public Health, 2022;10:917128.
PMID: 36408035 DOI: 10.3389/fpubh.2022.917128

Background: Assessment of the quality of life (QoL) among healthcare workers (HCWs) is vital for better healthcare and is an essential indicator for competent health service delivery. Since the coronavirus disease 2019 (COVID-19) pandemic strike, the frontline position of HCWs subjected them to tremendous mental and psychological burden with a high risk of virus acquisition.
Aim: This study evaluated the QoL and its influencing factors among HCWs residing in the Arab countries.
Methods: This was a cross-sectional study using a self-administered online questionnaire based on the World Health Organization QoL-BREF instrument with additional questions related to COVID-19. The study was conducted in three different languages (Arabic, English, and French) across 19 Arab countries between February 22 and March 24, 2022.
Results: A total of 3,170 HCWs were included in the survey. The majority were females (75.3%), aged 18-40 years (76.4%), urban residents (90.4%), married (54.5%), and were living in middle-income countries (72.0%). The mean scores of general health and general QoL were 3.7 ± 1.0 and 3.7 ± 0.9, respectively. Those who attained average physical, psychological, social, and environmental QoL were 40.8, 15.4, 26.2, and 22.3%, respectively. The income per capita and country income affected the mean scores of all QoL domains. Previous COVID-19 infection, having relatives who died of COVID-19, and being vaccinated against COVID-19 significantly affected the mean scores of different domains.
Conclusion: A large proportion of the Arab HCWs evaluated in this study had an overall poor QoL. More attention should be directed to this vulnerable group to ensure their productivity and service provision.
Fulltext Prioritisation Assessment and Robust Predictive System for Medical Equipment: A Comprehensive Strategic Maintenance Management

Zamzam AH, Al-Ani AKI, Wahab AKA, Lai KW, Satapathy SC, Khalil A, et al.

Front Public Health, 2021;9:782203.
PMID: 34869194 DOI: 10.3389/fpubh.2021.782203

The advancement of technology in medical equipment has significantly improved healthcare services. However, failures in upkeeping reliability, availability, and safety affect the healthcare services quality and significant impact can be observed in operations' expenses. The effective and comprehensive medical equipment assessment and monitoring throughout the maintenance phase of the asset life cycle can enhance the equipment reliability, availability, and safety. The study aims to develop the prioritisation assessment and predictive systems that measure the priority of medical equipment's preventive maintenance, corrective maintenance, and replacement programmes. The proposed predictive model is constructed by analysing features of 13,352 medical equipment used in public healthcare clinics in Malaysia. The proposed system comprises three stages: prioritisation analysis, model training, and predictive model development. In this study, we proposed 16 combinations of novel features to be used for prioritisation assessment and prediction of preventive maintenance, corrective maintenance, and replacement programme. The modified k-Means algorithm is proposed during the prioritisation analysis to automatically distinguish raw data into three main clusters of prioritisation assessment. Subsequently, these clusters are fed into and tested with six machine learning algorithms for the predictive prioritisation system. The best predictive models for medical equipment's preventive maintenance, corrective maintenance, and replacement programmes are selected among the tested machine learning algorithms. Findings indicate that the Support Vector Machine performs the best in preventive maintenance and replacement programme prioritisation predictive systems with the highest accuracy of 99.42 and 99.80%, respectively. Meanwhile, K-Nearest Neighbour yielded the highest accuracy in corrective maintenance prioritisation predictive systems with 98.93%. Based on the promising results, clinical engineers and healthcare providers can widely adopt the proposed prioritisation assessment and predictive systems in managing expenses, reporting, scheduling, materials, and workforce.
Fulltext Psychometrics of Persian Version of the Ageism Survey Among an Iranian Older Adult Population During COVID-19 Pandemic

Sharif Nia H, She L, Rasiah R, Khoshnavay Fomani F, Kaveh O, Pahlevan Sharif S, et al.

Front Public Health, 2021;9:683291.
PMID: 34869136 DOI: 10.3389/fpubh.2021.683291

Background: Studies have revealed an increase in discrimination, neglect, and abuse among the older adult population during this period. This study assessed the validity and reliability of the Persian version of the ageism survey instrument tested on a sample of the Iranian older adult population during coronavirus disease (COVID-19) pandemic. An important move in counteracting ageism is to classify the ageism scale comprehensively by employing adequate psychometrics. Methods: The Persian version of the ageism scale was developed using a two-step procedure. The first step involved translating and revising the original scale to develop a Persian version of the ageism scale. The second step involved assessing the psychometric features of the newly adapted scale using construct validity through exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) and thereafter assessing the reliability through the average inter-item correlation (AIC), Cronbach's alpha. The sample consisted of 400 older adults (age 65 and older), who were recruited through online data collection, with samples for EFA and CFA randomly selected from the total samples. Results: The Persian version of the ageism survey has three factors: age-related deprivation with five items, dignity with three items, and employment with three items; all of which explained 57.02% of the total variance. The outcome of the EFA was verified by the CFA, with internal consistency reliability being excellent (Cronbach's alpha was 0.725, 0.698, and 0.708 for the three factors). Conclusion: This study specifically offers a restructured three factors Persian version of the ageism survey for Iranian older adults with acceptable construct validity and reliability.
Fulltext Prevalence, Circumstances, and Risk Factors of Falls Among Community Dwelling Members of University of the Third Age

Ashari A, Hamid TA, Hussain MR, Ibrahim R, Hill KD

Front Public Health, 2021;9:610504.
PMID: 34900882 DOI: 10.3389/fpubh.2021.610504

Objective: Study aimed to identify the prevalence of falls and associated contributory factors among older Malaysians. Methods: A cross sectional study among community dwelling older adults aged 50 years and above. Self-administered questionnaires on history of falls in the previous 12 months, physical assessment and computerized and clinical measures of balance were assessed on a single occasion. Results: Forty nine (31.0%) participants fell, with 4.4% reported having multiple falls within the previous 12 months. Slips were the most prevalent cause of falls, accounting for 49% of falls. More than half (54.5%) of falls occurred in the afternoon while participants walked inside the home (32.7%), outside home (30.6%), and 36.7% were in community areas. More than half of respondents were identified as having turning instability. Step Test, turn sway, depression, physical activity level and edge contrast sensitivity were significantly worse for fallers (p < 0.05). Multiple logistic regression analysis showed that turning performance, visual acuity and back pain were significantly associated with falls risk, accounting for 72% of the variance of risk factors for falls among studied population. Conclusion: Falls are common among community dwelling older Malaysians. The findings provide information of falls and falls risk factors among community dwelling older adults in Malaysia. Future intervention studies should target locally identified falls risk factors. This study has highlighted the importance of instability during turning as an important fall risk factor.
Fulltext Psychometric Properties of the Persian Version of the Center for Epidemiological Studies Depression Scale Among the Iranian Public People During COVID-19 Pandemic

Sharif Nia H, Rahmatpour P, Sivarajan Froelicher E, Pahlevan Sharif S, Kaveh O, Rezazadeh Fazeli A, et al.

Front Public Health, 2021;9:728904.
PMID: 34970522 DOI: 10.3389/fpubh.2021.728904

Background: Several studies indicate a high prevalence of depression around the world during the period of the COVID-19 pandemic. Using a valid instrument to capture the depression of an individual in this situation is both important and timely. The present study aims to evaluate the psychometric properties of the Persian version of the Center for Epidemiological Studies Depression Scale (CES-D) among the public during the COVID-19 pandemic in Iran. Method: This is a cross-sectional study that was conducted in the Iranian population (n = 600) from April to July 2020. A two-part online form was used: sociodemographic characteristics and depression items (CES-D). The construct validity and internal consistency reliability of the scale were evaluated. Result: The results of the exploratory factor analysis illustrated two factors with 43.35% of the total variance of the depression were explained. Confirmatory factor analysis indicated that this model fits well. Internal consistency reliability was evaluated, and it was acceptable. Conclusion: The findings demonstrated that, in the Iranian sample, this depression scale yielded two factors (somatic and positive affects) solutions with suitable psychometric properties.
Fulltext Impact of the COVID-19 Pandemic on Cancer Researchers in 2020: A Qualitative Study of Events to Inform Mitigation Strategies

Fox L, Beyer K, Rammant E, Morcom E, Van Hemelrijck M, Sullivan R, et al.

Front Public Health, 2021;9:741223.
PMID: 34966713 DOI: 10.3389/fpubh.2021.741223

Introduction: The COVID-19 pandemic has had an unprecedented impact on global health systems and economies. With ongoing and future challenges posed to the field due to the pandemic, re-examining research priorities has emerged as a concern. As part of a wider project aiming to examine research priorities, here we aimed to qualitatively examine the documented impacts of the COVID-19 pandemic on cancer researchers. Materials and Methods: We conducted a literature review with the aim of identifying non-peer-reviewed journalistic sources and institutional blog posts which qualitatively documented the effects of the COVID-19 pandemic on cancer researchers. We searched on 12th January 2021 using the LexisNexis database and Google, using terms and filters to identify English-language media reports and blogs, containing references to both COVID-19 and cancer research. The targeted search returned 751 results, of which 215 articles met the inclusion criteria. These 215 articles were subjected to a conventional qualitative content analysis, to document the impacts of the pandemic on the field of cancer research. Results: Our analysis yielded a high plurality of qualitatively documented impacts, from which seven categories of direct impacts emerged: (1) COVID measures halting cancer research activity entirely; (2) COVID measures limiting cancer research activity; (3) forced adaptation of research protocols; (4) impacts on cancer diagnosis, cases, and services; (5) availability of resources for cancer research; (6) disruption to the private sector; and (7) disruption to supply chains. Three categories of consequences from these impacts also emerged: (1) potential changes to future research practice; (2) delays to the progression of the field; and (3) potential new areas of research interest. Discussion: The COVID-19 pandemic had extensive practical and economic effects on the field of cancer research in 2020 that were highly plural in nature. Appraisal of cancer research strategies in a post-COVID world should acknowledge the potential for substantial limitations (such as on financial resources, limited access to patients for research, decreased patient access to cancer care, staffing issues, administrative delays, or supply chain issues), exacerbated cancer disparities, advances in digital health, and new areas of research related to the intersection of cancer and COVID-19.
Fulltext Ageing Population's Impact on Economic Growth in Malaysia From 1981 to 2019: Evidence From an Autoregressive Distributed Lag Approach

Mohd SNA, Ishak AA, Selvaratnam DP

Front Public Health, 2021;9:731554.
PMID: 35004564 DOI: 10.3389/fpubh.2021.731554

This study investigates the impact of the ageing population on the economic growth for short- and long-run estimations in Malaysia, by using time series data from 1981 to 2019. This study adopts the autoregressive distributed lag (ARDL) method with the Bound test approach for the long-run estimation and the vector error correction model for the short-run estimation. Several econometric diagnostic tests were applied for validation and the appropriate model specification basis. The estimated result of this work indicates that the age dependency ratio proxy for the ageing population variable has a significant negative impact on economic growth in Malaysia. A 1% increase in old age dependency will decline gross domestic product's (GDP's) growth by an average of 6.6043% at the 5% level of significance. Hence, an increase in the ageing population will impede economic growth. Although controlled variables (e.g., physical capital, labour participation, and human capital) have a significant positive impact on economic growth in Malaysia, there is evidence of a long- and short-run relationship between economic growth and the ageing population variable, and also the control variable.
Fulltext Assessment of Impact of Containment During the COVID-19 Epidemic and Coping Behaviours Using Newly Developed Assessment Tools

Wong LP, Alias H, Danaee M, Lee HY, Tan KM, Tok PSK, et al.

Front Public Health, 2021;9:787672.
PMID: 35004587 DOI: 10.3389/fpubh.2021.787672

Background: The confinement measures during COVID-19 had a massive effect on physical and psychological health in public. This study assessed the impact of containment and coping behaviour among the Malaysia public during the COVID-19 pandemic. Questions assessing the impact of containment and coping behaviours were developed and psychometrically tested. Methods: Exploratory factor analysis (EFA) was conducted with the items using principal component analysis extraction and Varimax rotation. Partial least squares structural equation modelling was used to determine the relationship between coping and impact. Results: The 13-item of impact and 10-item coping instruments were developed with three dimensions identified through EFA. Both scales demonstrated excellent composite reliability and good convergent validity. The survey findings revealed that the impact on individual psychological aspects was prominent, followed by well-being and lifestyle. Mindfulness and physical coping strategies were most commonly reported. Coping through seeking help from health professionals and hotlines had a positive direct effect on well-being and lifestyle (b = 0.231, p < 0.001), psychological (B = 0.132, p < 0.001), and employment-related (0.194, p < 0.001) impacts. Coping through mindfulness practise had a negative effect on well-being and lifestyle-related impact (B = -0.180, p < 0.001) and employment-related impact (B = -0.096, p = 0.008). Conclusions: Despite some limitation, the scales for measuring impact and coping behaviours have the potential to be used as a measurement tool in future studies. Findings highlight the enormous impact of the pandemic on psychological well-being and lifestyles. Health authorities should support individual coping as it was found to be an important resilience-related factor to mitigate the impacts of containment during the pandemic.
Fulltext Profile and Predictors of Maternal Quality of Life During Physiological Pregnancy: A Cross-Sectional Analysis

Ishaq R, Shoaib M, Baloch NS, Sadiq A, Raziq A, Huma ZE, et al.

Front Public Health, 2021;9:801035.
PMID: 35111720 DOI: 10.3389/fpubh.2021.801035

Background: Quality of Life (QoL) and its determinants are significant in all stages of life, including pregnancy. The physical and emotional changes during pregnancy affect the QoL of pregnant women, affecting both maternal and infant health. Hence, assessing the QoL of pregnant women is gaining interest in literature. We, therefore, aimed to describe the QoL of pregnant women during physiological pregnancy and to identify its associated predictors in women attending a public healthcare institute of Quetta city, Pakistan.
Methods: A cross-sectional study was conducted at the Obstetrics and Gynecology Department of Sandeman Provincial Hospital Quetta city, Pakistan. The respondents were asked to answer the Urdu (lingua franca of Pakistan) version of the Quality of Life Questionnaire for Physiological Pregnancy. Data were coded and analyzed by SPPS v 21. The Kolmogorov-Smirnov test was used to establish normality of the data and non-parametric tests were used accordingly. Quality of Life was assessed as proposed by the developers. The Chi-square test was used to identify significant associations and linear regression was used to identify the predictors of QoL. For all analyses, p < 0.05 was taken significantly.
Results: Four hundred and three pregnant women participated in the study with a response rate of 98%. The mean QoL score was 19.85 ± 4.89 indicating very good QoL in the current cohort. The Chi-Square analysis reported a significant association between age, education, occupation, income, marital status, and trimester. Education was reported as a positive predictor for QoL (p = 0.006, β = 2.157). On the other hand, trimester was reported as a negative predictor of QoL (p = 0.013, β = -1.123).
Conclusion: Improving the QoL among pregnant women requires better identification of their difficulties and guidance. The current study highlighted educational status and trimester as the predictors of QoL in pregnant women. Health care professionals and policymakers should consider the identified factors while designing therapeutic plans and interventions for pregnant women.
Fulltext Fischer Linear Discrimination and Quadratic Discrimination Analysis-Based Data Mining Technique for Internet of Things Framework for Healthcare

Hasan MK, Ghazal TM, Alkhalifah A, Abu Bakar KA, Omidvar A, Nafi NS, et al.

Front Public Health, 2021;9:737149.
PMID: 34712639 DOI: 10.3389/fpubh.2021.737149

The internet of reality or augmented reality has been considered a breakthrough and an outstanding critical mutation with an emphasis on data mining leading to dismantling of some of its assumptions among several of its stakeholders. In this work, we study the pillars of these technologies connected to web usage as the Internet of things (IoT) system's healthcare infrastructure. We used several data mining techniques to evaluate the online advertisement data set, which can be categorized as high dimensional with 1,553 attributes, and the imbalanced data set, which automatically simulates an IoT discrimination problem. The proposed methodology applies Fischer linear discrimination analysis (FLDA) and quadratic discrimination analysis (QDA) within random projection (RP) filters to compare our runtime and accuracy with support vector machine (SVM), K-nearest neighbor (KNN), and Multilayer perceptron (MLP) in IoT-based systems. Finally, the impact on number of projections was practically experimented, and the sensitivity of both FLDA and QDA with regard to precision and runtime was found to be challenging. The modeling results show not only improved accuracy, but also runtime improvements. When compared with SVM, KNN, and MLP in QDA and FLDA, runtime shortens by 20 times in our chosen data set simulated for a healthcare framework. The RP filtering in the preprocessing stage of the attribute selection, fulfilling the model's runtime, is a standpoint in the IoT industry. Index Terms: Data Mining, Random Projection, Fischer Linear Discriminant Analysis, Online Advertisement Dataset, Quadratic Discriminant Analysis, Feature Selection, Internet of Things.
Fulltext Effects of Smart City Construction on the Quality of Public Occupational Health: Empirical Evidence From Guangdong Province, China

Cheng H, Wang FF, Dong DW, Liang JC, Zhao CF, Yan B

Front Public Health, 2021;9:769687.
PMID: 34746088 DOI: 10.3389/fpubh.2021.769687

This article takes the Guangdong Province of China as the research object and uses the difference-in-difference model to evaluate the impact of smart city construction on the quality of public occupational health and intercity differences. The obtained results show that smart city construction significantly improves the quality of public occupational health, and it is still valid after a series of robustness tests. The effect of this policy is stronger in cities that belong to the Pearl River Delta region or sub-provincial level cities. This study indicates that the central government should improve the pilot evaluation system and the performance appraisal mechanism of smart cities from the perspective of top-level design during the process of promoting smart city construction, which aims to correctly guide local governments to promote the construction of smart cities. To achieve the full improvement effect of smart city construction on the quality of public occupational health, local governments should implement smart city strategies in a purposeful and planned way according to the actual situation of the development of the jurisdiction.
Fulltext A Cross-Sectional Assessment of Urinary Tract Infections Among Geriatric Patients: Prevalence, Medication Regimen Complexity, and Factors Associated With Treatment Outcomes

Akhtar A, Ahmad Hassali MA, Zainal H, Ali I, Khan AH

Front Public Health, 2021;9:657199.
PMID: 34733812 DOI: 10.3389/fpubh.2021.657199

Background: Urinary tract infections (UTIs) are the second most prevalent infection among the elderly population. Hence, the current study aimed to evaluate the prevalence of UTIs among older adults, medication regimen complexity, and the factors associated with the treatment outcomes of elderly patients infected with UTIs. Methods: A retrospective cross-sectional study was conducted at the Department of Urology, Hospital Pulau Pinang, Malaysia. The patients ≥65 years of age were included in the present study with a confirmed diagnosis of UTIs from 2014 to 2018 (5 years). Results: A total of 460 patients met the inclusion criteria and were included in the present study. Cystitis (37.6%) was the most prevalent UTI among the study population followed by asymptomatic bacteriuria (ASB) (31.9%), pyelonephritis (13.9%), urosepsis (10.2%), and prostatitis (6.4%). Unasyn (ampicillin and sulbactam) was used to treat the UTIs followed by Bactrim (trimethoprim/sulfamethoxazole), and ciprofloxacin. The factors associated with the treatment outcomes of UTIs were gender (odd ratio [OR] = 1.628; p = 0.018), polypharmacy (OR = 0.647; p = 0.033), and presence of other comorbidities (OR = 2.004; p = 0.002) among the study population. Conclusion: Cystitis is the most common UTI observed in older adults. Gender, the burden of polypharmacy, and the presence of comorbidities are the factors that directly affect the treatment outcomes of UTIs among the study population.
Fulltext An Empirical Model to Predict the Diabetic Positive Using Stacked Ensemble Approach

R S, M S, Hasan MK, Saeed RA, Alsuhibany SA, Abdel-Khalek S

Front Public Health, 2021;9:792124.
PMID: 35127623 DOI: 10.3389/fpubh.2021.792124

Today, disease detection automation is widespread in healthcare systems. The diabetic disease is a significant problem that has spread widely all over the world. It is a genetic disease that causes trouble for human life throughout the lifespan. Every year the number of people with diabetes rises by millions, and this affects children too. The disease identification involves manual checking so far, and automation is a current trend in the medical field. Existing methods use a single algorithm for the prediction of diabetes. For complex problems, a single model is not enough because it may not be suitable for the input data or the parameters used in the approach. To solve complex problems, multiple algorithms are used. These multiple algorithms follow a homogeneous model or heterogeneous model. The homogeneous model means the same algorithm, but the model has been used multiple times. In the heterogeneous model, different algorithms are used. This paper adopts a heterogeneous ensemble model called the stacked ensemble model to predict whether a person has diabetes positively or negatively. This stacked ensemble model is advantageous in the prediction. Compared to other existing models such as logistic regression Naïve Bayes (72), (74.4), and LDA (81%), the proposed stacked ensemble model has achieved 93.1% accuracy in predicting blood sugar disease.
Fulltext Commentary: Outbreak of Chikungunya in Pakistan

Mallhi TH, Khan YH, Khan AH, Tanveer N, Khan OH, Aftab RA

Front Public Health, 2017;5:261.
PMID: 29034228 DOI: 10.3389/fpubh.2017.00261
Fulltext Health Literacy-Related Knowledge, Attitude, and Perceived Barriers: A Cross-sectional Study among Physicians, Pharmacists, and Nurses in Public Hospitals of Penang, Malaysia

Rajah R, Hassali MA, Lim CJ

Front Public Health, 2017;5:281.
PMID: 29098146 DOI: 10.3389/fpubh.2017.00281

Introduction: Patients' health literacy (HL) has emerged as a critical determinant of health outcomes and becoming one of the core competencies of health-care providers. Therefore, this study aimed to assess among Malaysian physicians, pharmacists, and nurses, their HL-related knowledge, attitude, and perceived barriers, and also to determine the associated factors.
Methods: A cross-sectional study design was used to enroll 600 eligible respondents using stratified sampling from 6 public hospitals in Penang, Malaysia. A validated self-administered questionnaire was used for data collection. Descriptive and inferential analysis was performed with statistical significance defined as p

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