Displaying publications 141 - 160 of 1340 in total

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  1. Fuller JF
    N Z Dent J, 1977 Apr;73(332):71-6.
    PMID: 267854
    Matched MeSH terms: Developing Countries*
  2. LLEWELLYN-JONES D
    Med J Malaya, 1962 Jun;16:260-6.
    PMID: 14466036
    Matched MeSH terms: Developing Countries*
  3. Vedanthan R, Bernabe-Ortiz A, Herasme OI, Joshi R, Lopez-Jaramillo P, Thrift AG, et al.
    Cardiol Clin, 2017 Feb;35(1):99-115.
    PMID: 27886793 DOI: 10.1016/j.ccl.2016.08.010
    Elevated blood pressure, a major risk factor for ischemic heart disease, heart failure, and stroke, is the leading global risk for mortality. Treatment and control rates are very low in low- and middle-income countries. There is an urgent need to address this problem. The Global Alliance for Chronic Diseases sponsored research projects focus on controlling hypertension, including community engagement, salt reduction, salt substitution, task redistribution, mHealth, and fixed-dose combination therapies. This paper reviews the rationale for each approach and summarizes the experience of some of the research teams. The studies demonstrate innovative and practical methods for improving hypertension control.
    Matched MeSH terms: Developing Countries*
  4. Saleem F, Hasaali MA, Ul Haq N
    Res Social Adm Pharm, 2016 09 14;13(1):253.
    PMID: 27720437 DOI: 10.1016/j.sapharm.2016.09.001
    Matched MeSH terms: Developing Countries*
  5. Poudel A, Kc B, Shrestha S, Nissen L
    J Glob Health, 2019 12;9(2):020309.
    PMID: 31656599 DOI: 10.7189/jogh.09.020309
    Matched MeSH terms: Developing Countries*
  6. Lee KS, Ming LC, Lean QY, Yee SM, Patel R, Taha NA, et al.
    J Epidemiol Glob Health, 2019 06;9(2):93-97.
    PMID: 31241865 DOI: 10.2991/jegh.k.190506.001
    Matched MeSH terms: Developing Countries*
  7. Karmegam, Karuppiah, Salit MS, Ismail MY, Ismail N, Tamrin SB, et al.
    J Hum Ergol (Tokyo), 2011 Dec;40(1-2):37-46.
    PMID: 25665206 DOI: 10.11183/jhe.40.37
    This paper presents the results of an anthropometric data collected from polytechnic students in Malaysia. A total of 1032 (595 males and 437 females) students participated in the study. Their ages ranged from 18 to 24 years. A total of 34 anthropometric dimensions were measured. Descriptive statistics such as mean, standard deviation, standard error of mean, coefficient of variation, minimum, maximum and percentile for each parameter were estimated. In addition, the comparison between Malaysia anthropometric data and Thailand (South) anthropometric data were also presented. The results show that there is a total of 12 and 11 (of dimensions parameters) significant differences (p < 0.05) between the male and female adults respectively.
    Matched MeSH terms: Developing Countries*
  8. Mahathevan R
    J Hum Ergol (Tokyo), 1982;11 Suppl:139-45.
    PMID: 7188450 DOI: 10.11183/jhe1972.11.Supplement_139
    Matched MeSH terms: Developing Countries*
  9. Alibudbud R
    Asian J Psychiatr, 2022 Dec;78:103311.
    PMID: 36335844 DOI: 10.1016/j.ajp.2022.103311
    This infodemiological study utilized Relative Search Volumes (RSV) from Google Trends. It determined changes in public interest in mental health after the implementation of the mental health laws of Malaysia, the Philippines, Singapore, and Thailand using search volumes from 2004 to 2021. It found that public interest in mental health increased in Malaysia, the Philippines, and Singapore after implementing their mental health laws. On the contrary, public interest in mental health continued to decrease in Thailand despite its mental health law implementation. This can be explained by the unequal prioritization of mental health among these countries.
    Matched MeSH terms: Developing Countries*
  10. Fleming KA, Horton S, Wilson ML, Atun R, DeStigter K, Flanigan J, et al.
    Lancet, 2021 Nov 27;398(10315):1997-2050.
    PMID: 34626542 DOI: 10.1016/S0140-6736(21)00673-5
    Matched MeSH terms: Developing Countries*
  11. Solarin SA, Al-Mulali U, Gan GGG, Shahbaz M
    Environ Sci Pollut Res Int, 2018 Aug;25(23):22641-22657.
    PMID: 29846898 DOI: 10.1007/s11356-018-2392-5
    The aim of this research is to explore the effect of biomass energy consumption on CO2 emissions in 80 developed and developing countries. To achieve robustness, the system generalised method of moment was used and several control variables were incorporated into the model including real GDP, fossil fuel consumption, hydroelectricity production, urbanisation, population, foreign direct investment, financial development, institutional quality and the Kyoto protocol. Relying on the classification of the World Bank, the countries were categorised to developed and developing countries. We also used a dynamic common correlated effects estimator. The results consistently show that biomass energy as well as fossil fuel consumption generate more CO2 emissions. A closer look at the results show that a 100% increase in biomass consumption (tonnes per capita) will increase CO2 emissions (metric tons per capita) within the range of 2 to 47%. An increase of biomass energy intensity (biomass consumption in tonnes divided by real gross domestic product) of 100% will increase CO2 emissions (metric tons per capita) within the range of 4 to 47%. An increase of fossil fuel consumption (tonnes of oil equivalent per capita) by 100% will increase CO2 emissions (metric tons per capita) within the range of 35 to 55%. The results further show that real GDP urbanisation and population increase CO2 emissions. However, hydroelectricity and institutional quality decrease CO2 emissions. It is further observed that financial development, foreign direct investment and openness decrease CO2 emissions in the developed countries, but the opposite results are found for the developing nations. The results also show that the Kyoto Protocol reduces emission and that Environmental Kuznets Curve exists. Among the policy implications of the foregoing results is the necessity of substituting fossil fuels with other types of renewable energy (such as hydropower) rather than biomass energy for reduction of emission to be achieved.
    Matched MeSH terms: Developing Countries*
  12. Tham KW, Abdul Ghani R, Cua SC, Deerochanawong C, Fojas M, Hocking S, et al.
    Obes Rev, 2023 Feb;24(2):e13520.
    PMID: 36453081 DOI: 10.1111/obr.13520
    Obesity is a chronic disease in which the abnormal or excessive accumulation of body fat leads to impaired health and increased risk of mortality and chronic health complications. Prevalence of obesity is rising rapidly in South and Southeast Asia, with potentially serious consequences for local economies, healthcare systems, and quality of life. Our group of obesity specialists from Bangladesh, Brunei Darussalam, India, Indonesia, Malaysia, Philippines, Singapore, Sri Lanka, Thailand, and Viet Nam undertook to develop consensus recommendations for management and care of adults and children with obesity in South and Southeast Asia. To this end, we identified and researched 12 clinical questions related to obesity. These questions address the optimal approaches for identifying and staging obesity, treatment (lifestyle, behavioral, pharmacologic, and surgical options) and maintenance of reduced weight, as well as issues related to weight stigma and patient engagement in the clinical setting. We achieved consensus on 42 clinical recommendations that address these questions. An algorithm describing obesity care is presented, keyed to the various consensus recommendations.
    Matched MeSH terms: Developing Countries*
  13. Teh J, Mazlan M, Danaee M, Waran RJ, Waran V
    PLoS One, 2023;18(9):e0284484.
    PMID: 37703233 DOI: 10.1371/journal.pone.0284484
    OBJECTIVE: Road traffic accident (RTA) is the major cause of traumatic brain injury (TBI) in developing countries and affects mostly young adult population. This research aimed to describe the factors predicting functional outcome after TBI caused by RTA in a Malaysian setting.

    METHODS: This was a retrospective cross-sectional study conducted on specialist medical reports written from 2009 to 2019, involving patients who survived after TBI from RTA. The functional outcome was assessed using the Glasgow Outcome Scale-Extended (GOSE). Factors associated with good outcome were analysed via logistic regression analysis. Multivariate logistic regression analysis was used to derive the best fitting Prediction Model and split-sample cross-validation was performed to develop a prediction model.

    RESULTS: A total of 1939 reports were evaluated. The mean age of the study participants was 32.4 ± 13.7 years. Most patients were male, less than 40, and with average post RTA of two years. Good outcome (GOSE score 7 & 8) was reported in 30.3% of the patients. Factors significantly affecting functional outcome include age, gender, ethnicity, marital status, education level, severity of brain injury, neurosurgical intervention, ICU admission, presence of inpatient complications, cognitive impairment, post-traumatic headache, post traumatic seizures, presence of significant behavioural issue; and residence post discharge (p<0.05). After adjusting for confounding factors, prediction model identified age less than 40, mild TBI, absence of post traumatic seizure, absence of behaviour issue, absence of cognitive impairment and independent living post TBI as significant predictors of good functional outcome post trauma. Discrimination of the model was acceptable (C-statistic, 0.67; p<0.001, 95% CI: 0.62-0.73).

    CONCLUSION: Good functional outcome following TBI due to RTA in this study population is comparable to other low to middle income countries but lower than high income countries. Factors influencing outcome such as seizure, cognitive and behavioural issues, and independent living post injury should be addressed early to achieve favourable long-term outcomes.

    Matched MeSH terms: Developing Countries*
  14. Abbasi GA, Tiew LY, Tang J, Goh YN, Thurasamy R
    PLoS One, 2021;16(3):e0247582.
    PMID: 33684120 DOI: 10.1371/journal.pone.0247582
    In recent years, the growth of cryptocurrency has undergone an enormous increase in cryptocurrency markets all around the world. Sadly, only insignificant heed has been paid to the unveiling of determinants of cryptocurrency adoption globally, particularly in emerging markets like Malaysia. The purpose of the study is to examine whether the application of deep learning-based dual-stage Partial Least Square-Structural Equation Modelling (PLS-SEM) & Artificial Neural Network (ANN) analysis enable better in-depth research results as compared to single-step PLS-SEM approach and to excavate factors which can predict behavioural intention to adopt cryptocurrency. The Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model were extended with the inclusion of trust and personnel innovativeness. The model was further validated by introducing a new path model compared to the original UTAUT2 model and the moderating role of personal innovativeness between performance expectancy and price value, with a sample of 314 respondents. Contrary to previous technology adoption studies that used PLS-SEM & ANN as single-stage analysis, this study further enhanced the analysis by applying a deep learning-based dual-stage PLS-SEM and ANN method. The application of deep learning-based dual-stage PLS-SEM & ANN analysis is a novel methodological approach, detecting both linear and non-linear associations among constructs. At the same time, it is regarded as a superior statistical approach as compared to traditional hybrid shallow SEM & ANN single-stage analysis. Also, sensitivity analysis provides normalised importance using multi-layer perceptron with the feed-forward-back-propagation algorithm. Furthermore, the deep learning-based dual-stage PLS-SEM & ANN revealed that trust proved to be the strongest predictor in driving user intention. The introduction of this new methodology and the theoretical contribution opens the vistas of the extant body of knowledge in technology-adoption related literature. This study also provides theoretical, practical and methodological contributions.
    Matched MeSH terms: Developing Countries/economics*
  15. Yap CK, Ismail A, Tan SG, Omar H
    Environ Int, 2002 Dec;28(6):467-79.
    PMID: 12503912
    Malaysia is now a developing country and on her way towards being an industrialised one by the year 2020. Most of her industries and urban areas are located on the west coast of Peninsular Malaysia. In addition, the offshore area of the west coast is now one of the busiest shipping lanes in the world. These two phenomena make the intertidal and offshore areas of the west coast of Peninsular Malaysia interesting for scientific studies. Therefore, this study focused on both the offshore and intertidal sediments of the west coast of Peninsular Malaysia. Sampling for sediment samples were done from the northern to the southern ends of the peninsula and these sediment samples were analysed for Cu and Pb. It was found that total Cu concentrations ranged from 0.25 to 13.8 and 0.40 to 315 microg/g dry weight (dw) for offshore and intertidal sediments, respectively. For Pb, it ranged from 3.59 to 25.4 and 0.96 to 69.8 microg/g dw for the offshore and intertidal sediments, respectively. The ranges of Cu and Pb found from the west coast of Peninsular Malaysia were low in comparison to regional data. However, some intertidal areas were identified as receiving anthropogenic Cu and Pb. Geochemical studies revealed that the 'nonresistant' fraction for Pb contributed about 70.0% to 75.0% and 54.0% of the total Pb concentration in the offshore and intertidal sediments, respectively. As for Cu, the 'nonresistant' fraction contributed about 46.2% to 60.4% and 46.3% of the total Cu concentration in the offshore and intertidal sediments, respectively. The 'nonresistant' fraction contained mostly of anthropogenic metals besides natural origins. These 'nonresistant' percentages indicated that both the offshore and intertidal areas could have received anthropogenic-derived metals, which could be influenced by physico-chemical properties of the sediments. Although the present data indicated that contamination due to Cu and Pb in the west coast of Peninsular Malaysia especially in the offshore areas were not serious, regular biomonitoring studies along the west coast of Peninsular Malaysia are recommended.
    Matched MeSH terms: Developing Countries*
  16. Murad MW, Abdullah ABM, Islam MM, Alam MM, Reaiche C, Boyle S
    J Public Health Policy, 2023 Jun;44(2):230-241.
    PMID: 37117262 DOI: 10.1057/s41271-023-00413-w
    We investigated the macroeconomic determinants of neonatal, infant, and under-five mortalities in Bangladesh for the period 1991-2018 and discuss implications of the United Nations' Sustainable Development Goal 3 (SDG 3) and Millennium Development Goal 4 (MDG 4) for developing countries. We used annual time series data and the econometric techniques of Fully Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) regressions for analysis. Determinants most effective in combating neonatal, infant, and under-five mortalities include variables such as 'protecting newborns against tetanus', 'increasing healthcare expenditure', and 'making sure births are attended by skilled healthcare staff'. Employing more healthcare workers and assuring more and improved healthcare provisions can further reduce the neonatal, infant, and under-five mortalities. Developing countries with similar macroeconomic profiles can achieve similar SDG 3 and MDG 4 outcomes by emulating the policies and strategies Bangladesh applied to reducing child mortalities over the last three decades.
    Matched MeSH terms: Developing Countries*
  17. Lecky FE, Reynolds T, Otesile O, Hollis S, Turner J, Fuller G, et al.
    BMC Emerg Med, 2020 08 31;20(1):68.
    PMID: 32867675 DOI: 10.1186/s12873-020-00362-7
    BACKGROUND: More than half of deaths in low- and middle-income countries (LMICs) result from conditions that could be treated with emergency care - an integral component of universal health coverage (UHC) - through timely access to lifesaving interventions.

    METHODS: The World Health Organization (WHO) aims to extend UHC to a further 1 billion people by 2023, yet evidence supporting improved emergency care coverage is lacking. In this article, we explore four phases of a research prioritisation setting (RPS) exercise conducted by researchers and stakeholders from South Africa, Egypt, Nepal, Jamaica, Tanzania, Trinidad and Tobago, Tunisia, Colombia, Ethiopia, Iran, Jordan, Malaysia, South Korea and Phillipines, USA and UK as a key step in gathering evidence required by policy makers and practitioners for the strengthening of emergency care systems in limited-resource settings.

    RESULTS: The RPS proposed seven priority research questions addressing: identification of context-relevant emergency care indicators, barriers to effective emergency care; accuracy and impact of triage tools; potential quality improvement via registries; characteristics of people seeking emergency care; best practices for staff training and retention; and cost effectiveness of critical care - all within LMICs.

    CONCLUSIONS: Convened by WHO and facilitated by the University of Sheffield, the Global Emergency Care Research Network project (GEM-CARN) brought together a coalition of 16 countries to identify research priorities for strengthening emergency care in LMICs. Our article further assesses the quality of the RPS exercise and reviews the current evidence supporting the identified priorities.

    Matched MeSH terms: Developing Countries*
  18. Masood M, Reidpath DD
    PLoS One, 2017;12(6):e0178928.
    PMID: 28662041 DOI: 10.1371/journal.pone.0178928
    BACKGROUND: This study explores the relationship between BMI and national-wealth and the cross-level interaction effect of national-wealth and individual household-wealth using multilevel analysis.

    METHODS: Data from the World Health Survey conducted in 2002-2004, across 70 low-, middle- and high-income countries was used. Participants aged 18 years and over were selected using multistage, stratified cluster sampling. BMI was used as outcome variable. The potential determinants of individual-level BMI were participants' sex, age, marital-status, education, occupation, household-wealth and location(rural/urban) at the individual-level. The country-level factors used were average national income (GNI-PPP) and income inequality (Gini-index). A two-level random-intercepts and fixed-slopes model structure with individuals nested within countries was fitted, treating BMI as a continuous outcome.

    RESULTS: The weighted mean BMI and standard-error of the 206,266 people from 70-countries was 23.90 (4.84). All the low-income countries were below the 25.0 mean BMI level and most of the high-income countries were above. All wealthier quintiles of household-wealth had higher scores in BMI than lowest quintile. Each USD10000 increase in GNI-PPP was associated with a 0.4 unit increase in BMI. The Gini-index was not associated with BMI. All these variables explained 28.1% of country-level, 4.9% of individual-level and 7.7% of total variance in BMI. The cross-level interaction effect between GNI-PPP and household-wealth was significant. BMI increased as the GNI-PPP increased in first four quintiles of household-wealth. However, the BMI of the wealthiest people decreased as the GNI-PPP increased.

    CONCLUSION: Both individual-level and country-level factors made an independent contribution to the BMI of the people. Household-wealth and national-income had significant interaction effects.

    Matched MeSH terms: Developing Countries*
  19. Iskandar K, Molinier L, Hallit S, Sartelli M, Hardcastle TC, Haque M, et al.
    Antimicrob Resist Infect Control, 2021 03 31;10(1):63.
    PMID: 33789754 DOI: 10.1186/s13756-021-00931-w
    Data on comprehensive population-based surveillance of antimicrobial resistance is lacking. In low- and middle-income countries, the challenges are high due to weak laboratory capacity, poor health systems governance, lack of health information systems, and limited resources. Developing countries struggle with political and social dilemma, and bear a high health and economic burden of communicable diseases. Available data are fragmented and lack representativeness which limits their use to advice health policy makers and orientate the efficient allocation of funding and financial resources on programs to mitigate resistance. Low-quality data means soaring rates of antimicrobial resistance and the inability to track and map the spread of resistance, detect early outbreaks, and set national health policy to tackle resistance. Here, we review the barriers and limitations of conducting effective antimicrobial resistance surveillance, and we highlight multiple incremental approaches that may offer opportunities to strengthen population-based surveillance if tailored to the context of each country.
    Matched MeSH terms: Developing Countries*
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