Displaying all 8 publications

Abstract:
Sort:
  1. Tan HM, Tan WP, Wong JH, Ho CC, Teo CH, Ng CJ
    Korean J Urol, 2014 Nov;55(11):710-7.
    PMID: 25405012 DOI: 10.4111/kju.2014.55.11.710
    PURPOSE: The proposed Men's Health Index (MHI) aims to provide a practical and systematic framework for comprehensively assessing and stratifying older men with the intention of optimising their health and functional status.
    MATERIALS AND METHODS: A literature search was conducted using PubMed from 1980 to 2012. We specifically looked for instruments which: assess men's health, frailty and fitness; predict life expectancy, mortality and morbidities. The instruments were assessed by the researchers who then agreed on the tools to be included in the MHI. When there was disagreements, the researchers discussed and reached a consensus guided by the principle that the MHI could be used in the primary care setting targetting men aged 55-65 years.
    RESULTS: The instruments chosen include the Charlson's Combined Comorbidity-Age Index; the International Index of Erectile Function-5; the International Prostate Symptom Score; the Androgen Deficiency in Aging Male; the Survey of Health, Ageing and Retirement in Europe Frailty Instrument; the Sitting-Rising Test; the Senior Fitness Test; the Fitness Assessment Score; and the Depression Anxiety Stress Scale-21. A pilot test on eight men was carried out and showed that the men's health index is viable.
    CONCLUSIONS: The concept of assessing, stratifying, and optimizing men's health should be incorporated into routine health care, and this can be implemented by using the MHI. This index is particularly useful to primary care physicians who are in a strategic position to engage men at the peri-retirement age in a conversation about their life goals based on their current and predicted health status.
    KEYWORDS: Health status indicators; Men; Physical fitness; Retirement
    Matched MeSH terms: Life Expectancy/trends*
  2. GBD 2015 Mortality and Causes of Death Collaborators
    Lancet, 2016 Oct 08;388(10053):1459-1544.
    PMID: 27733281 DOI: 10.1016/S0140-6736(16)31012-1
    BACKGROUND: Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures.
    METHODS: We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography-year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER).
    FINDINGS: Globally, life expectancy from birth increased from 61·7 years (95% uncertainty interval 61·4-61·9) in 1980 to 71·8 years (71·5-72·2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11·3 years (3·7-17·4), to 62·6 years (56·5-70·2). Total deaths increased by 4·1% (2·6-5·6) from 2005 to 2015, rising to 55·8 million (54·9 million to 56·6 million) in 2015, but age-standardised death rates fell by 17·0% (15·8-18·1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14·1% (12·6-16·0) to 39·8 million (39·2 million to 40·5 million) in 2015, whereas age-standardised rates decreased by 13·1% (11·9-14·3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42·1%, 39·1-44·6), malaria (43·1%, 34·7-51·8), neonatal preterm birth complications (29·8%, 24·8-34·9), and maternal disorders (29·1%, 19·3-37·1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000-183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000-532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death.
    INTERPRETATION: At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems.
    FUNDING: Bill & Melinda Gates Foundation.
    Malaysian collaborators: Southern University College, Skudai, Malaysia (Y J Kim PhD); School of Medical Sciences, University of Science Malaysia, Kubang Kerian, Malaysia (K I Musa MD); Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur, Malaysia (R Sahathevan PhD); Department of Community Medicine, International Medical University, Kuala Lumpur, Malaysia (C T Sreeramareddy MD); WorldFish, Penang, Malaysia (A L Thorne-Lyman ScD)
    Matched MeSH terms: Life Expectancy/trends*
  3. Wang J, Jamison DT, Bos E, Vu MT
    Trop Med Int Health, 1997 Oct;2(10):1001-10.
    PMID: 9357491
    This paper analyses the effect of income and education on life expectancy and mortality rates among the elderly in 33 countries for the period 1960-92 and assesses how that relationship has changed over time as a result of technical progress. Our outcome variables are life expectancy at age 60 and the probability of dying between age 60 and age 80 for both males and females. The data are from vital-registration based life tables published by national statistical offices for several years during this period. We estimate regressions with determinants that include GDP per capita (adjusted for purchasing power), education and time (as a proxy for technical progress). As the available measure of education failed to account for variation in life expectancy or mortality at age 60, our reported analyses focus on a simplified model with only income and time as predictors. The results indicate that, controlling for income, mortality rates among the elderly have declined considerably over the past three decades. We also find that poverty (as measured by low average income levels) explains some of the variation in both life expectancy at age 60 and mortality rates among the elderly across the countries in the sample. The explained amount of variation is more substantial for females than for males. While poverty does adversely affect mortality rates among the elderly (and the strength of this effect is estimated to be increasing over time), technical progress appears far more important in the period following 1960. Predicted female life expectancy (at age 60) in 1960 at the mean income level in 1960 was, for example 18.8 years; income growth to 1992 increased this by an estimated 0.7 years, whereas technical progress increased it by 2.0 years. We then use the estimated regression results to compare country performance on life expectancy of the elderly, controlling for levels of poverty (or income), and to assess how performance has varied over time. High performing countries, on female life expectancy at age 60, for the period around 1990, included Chile (1.0 years longer life expectancy), China (1.7 years longer), France (2.0 years longer), Japan (1.9 years longer), and Switzerland (1.3 years longer). Poorly performing countries included Denmark (1.1 years shorter life expectancy than predicted from income), Hungary (1.4 years shorter), Iceland (1.2 years shorter), Malaysia (1.6 years shorter), and Trinidad and Tobago (3.9 years shorter). Chile and Switzerland registered major improvements in relative performance over this period; Norway, Taiwan and the USA, in contrast showed major declines in performance between 1980 and the early 1990s.
    Matched MeSH terms: Life Expectancy/trends*
  4. Kok JK, Yap YN
    J Aging Stud, 2014 Dec;31:54-61.
    PMID: 25456622 DOI: 10.1016/j.jaging.2014.08.007
    Longer lives and extended retirement have created a 'young old age' stage of life. How people spend their "young old age" has become increasingly important. This research aims to investigate the different ageing experiences of Japanese and Malaysian women and the activities they engaged in their "young old age". In-depth interviews were conducted to collect data and an adapted grounded theory approach was used for data analysis. Findings reveal many common characteristics for both groups of research participants. The emerging themes show that Japanese and Malaysian Chinese have different life missions evident in their daily activities, one passing on culture and the other passing on family values and life experience. They also differ in their choice of living arrangement (independent versus dependent/interdependent), attitudes to life (fighting versus accepting) and activities in which to engage (aesthetic pursuits versus family oriented activities).
    Matched MeSH terms: Life Expectancy/trends
  5. Phua KL
    Pac Health Dialog, 2009 Nov;15(2):117-27.
    PMID: 20443525
    Both the Maori of New Zealand and the Orang Asli of Malaysia are indigenous peoples who have been subjected to prejudice, discrimination and displacement in its various forms by other ethnic groups in their respective countries. However, owing to changes in the socio-political climate, they have been granted rights (including legal privileges) in more recent times. Data pertaining to the health and socio-economic status of the Maori and the Orang Asli are analysed to see if the granting of legal privileges has made any difference for the two communities. One conclusion is that legal privileges (and the granting of special status) do not appear to work well in terms of reducing health and socio-economic gaps.
    Matched MeSH terms: Life Expectancy/trends
  6. Roth GA, Johnson C, Abajobir A, Abd-Allah F, Abera SF, Abyu G, et al.
    J Am Coll Cardiol, 2017 Jul 04;70(1):1-25.
    PMID: 28527533 DOI: 10.1016/j.jacc.2017.04.052
    BACKGROUND: The burden of cardiovascular diseases (CVDs) remains unclear in many regions of the world.

    OBJECTIVES: The GBD (Global Burden of Disease) 2015 study integrated data on disease incidence, prevalence, and mortality to produce consistent, up-to-date estimates for cardiovascular burden.

    METHODS: CVD mortality was estimated from vital registration and verbal autopsy data. CVD prevalence was estimated using modeling software and data from health surveys, prospective cohorts, health system administrative data, and registries. Years lived with disability (YLD) were estimated by multiplying prevalence by disability weights. Years of life lost (YLL) were estimated by multiplying age-specific CVD deaths by a reference life expectancy. A sociodemographic index (SDI) was created for each location based on income per capita, educational attainment, and fertility.

    RESULTS: In 2015, there were an estimated 422.7 million cases of CVD (95% uncertainty interval: 415.53 to 427.87 million cases) and 17.92 million CVD deaths (95% uncertainty interval: 17.59 to 18.28 million CVD deaths). Declines in the age-standardized CVD death rate occurred between 1990 and 2015 in all high-income and some middle-income countries. Ischemic heart disease was the leading cause of CVD health lost globally, as well as in each world region, followed by stroke. As SDI increased beyond 0.25, the highest CVD mortality shifted from women to men. CVD mortality decreased sharply for both sexes in countries with an SDI >0.75.

    CONCLUSIONS: CVDs remain a major cause of health loss for all regions of the world. Sociodemographic change over the past 25 years has been associated with dramatic declines in CVD in regions with very high SDI, but only a gradual decrease or no change in most regions. Future updates of the GBD study can be used to guide policymakers who are focused on reducing the overall burden of noncommunicable disease and achieving specific global health targets for CVD.

    Matched MeSH terms: Life Expectancy/trends*
  7. Jiwa M, Othman S, Hanafi NS, Ng CJ, Khoo EM, Chia YC
    Qual Prim Care, 2012;20(5):317-20.
    PMID: 23113999
    Malaysia has achieved reasonable health outcomes even though the country spends a modest amount of Gross Domestic Product on healthcare. However, the country is now experiencing a rising incidence of both infectious diseases and chronic lifestyle conditions that reflect growing wealth in a vibrant and successful economy. With an eye on an ageing population, reform of the health sector is a government priority. As in other many parts of the world, general practitioners are the first healthcare professional consulted by patients. The Malaysian health system is served by public and private care providers. The integration of the two sectors is a key target for reform. However, the future health of the nation will depend on leadership in the primary care sector. This leadership will need to be informed by research to integrate care providers, empower patients, bridge cultural gaps and ensure equitable access to scarce health resources.
    Matched MeSH terms: Life Expectancy/trends
  8. Qureshi MI, Rasli AM, Awan U, Ma J, Ali G, Faridullah, et al.
    Environ Sci Pollut Res Int, 2015 Mar;22(5):3467-76.
    PMID: 25242593 DOI: 10.1007/s11356-014-3584-2
    The objective of the study is to establish the link between air pollution, fossil fuel energy consumption, industrialization, alternative and nuclear energy, combustible renewable and wastes, urbanization, and resulting impact on health services in Malaysia. The study employed two-stage least square regression technique on the time series data from 1975 to 2012 to possibly minimize the problem of endogeniety in the health services model. The results in general show that air pollution and environmental indicators act as a strong contributor to influence Malaysian health services. Urbanization and nuclear energy consumption both significantly increases the life expectancy in Malaysia, while fertility rate decreases along with the increasing urbanization in a country. Fossil fuel energy consumption and industrialization both have an indirect relationship with the infant mortality rate, whereas, carbon dioxide emissions have a direct relationship with the sanitation facility in a country. The results conclude that balancing the air pollution, environment, and health services needs strong policy vistas on the end of the government officials.
    Matched MeSH terms: Life Expectancy/trends
Filters
Contact Us

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links