Displaying publications 1 - 20 of 28 in total

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  1. Hobeika A, Stauffer MHT, Dub T, van Bortel W, Beniston M, Bukachi S, et al.
    Lancet Glob Health, 2023 Aug;11(8):e1301-e1307.
    PMID: 37474236 DOI: 10.1016/S2214-109X(23)00246-2
    The COVID-19 pandemic has shown the need for better global governance of pandemic prevention, preparedness, and response (PPR) and has emphasised the importance of organised knowledge production and uptake. In this Health Policy, we assess the potential values and risks of establishing an Intergovernmental Panel for One Health (IPOH). Similar to the Intergovernmental Panel on Climate Change, an IPOH would facilitate knowledge uptake in policy making via a multisectoral approach, and hence support the addressing of infectious disease emergence and re-emergence at the human-animal-environment interface. The potential benefits to pandemic PPR include a clear, unified, and authoritative voice from the scientific community, support to help donors and institutions to prioritise their investments, evidence-based policies for implementation, and guidance on defragmenting the global health system. Potential risks include a scope not encompassing all pandemic origins, unclear efficacy in fostering knowledge uptake by policy makers, potentially inadequate speed in facilitating response efforts, and coordination challenges among an already dense set of stakeholders. We recommend weighing these factors when designing institutional reforms for a more effective global health system.
  2. Rosengren A, Smyth A, Rangarajan S, Ramasundarahettige C, Bangdiwala SI, AlHabib KF, et al.
    Lancet Glob Health, 2019 06;7(6):e748-e760.
    PMID: 31028013 DOI: 10.1016/S2214-109X(19)30045-2
    BACKGROUND: Socioeconomic status is associated with differences in risk factors for cardiovascular disease incidence and outcomes, including mortality. However, it is unclear whether the associations between cardiovascular disease and common measures of socioeconomic status-wealth and education-differ among high-income, middle-income, and low-income countries, and, if so, why these differences exist. We explored the association between education and household wealth and cardiovascular disease and mortality to assess which marker is the stronger predictor of outcomes, and examined whether any differences in cardiovascular disease by socioeconomic status parallel differences in risk factor levels or differences in management.

    METHODS: In this large-scale prospective cohort study, we recruited adults aged between 35 years and 70 years from 367 urban and 302 rural communities in 20 countries. We collected data on families and households in two questionnaires, and data on cardiovascular risk factors in a third questionnaire, which was supplemented with physical examination. We assessed socioeconomic status using education and a household wealth index. Education was categorised as no or primary school education only, secondary school education, or higher education, defined as completion of trade school, college, or university. Household wealth, calculated at the household level and with household data, was defined by an index on the basis of ownership of assets and housing characteristics. Primary outcomes were major cardiovascular disease (a composite of cardiovascular deaths, strokes, myocardial infarction, and heart failure), cardiovascular mortality, and all-cause mortality. Information on specific events was obtained from participants or their family.

    FINDINGS: Recruitment to the study began on Jan 12, 2001, with most participants enrolled between Jan 6, 2005, and Dec 4, 2014. 160 299 (87·9%) of 182 375 participants with baseline data had available follow-up event data and were eligible for inclusion. After exclusion of 6130 (3·8%) participants without complete baseline or follow-up data, 154 169 individuals remained for analysis, from five low-income, 11 middle-income, and four high-income countries. Participants were followed-up for a mean of 7·5 years. Major cardiovascular events were more common among those with low levels of education in all types of country studied, but much more so in low-income countries. After adjustment for wealth and other factors, the HR (low level of education vs high level of education) was 1·23 (95% CI 0·96-1·58) for high-income countries, 1·59 (1·42-1·78) in middle-income countries, and 2·23 (1·79-2·77) in low-income countries (pinteraction<0·0001). We observed similar results for all-cause mortality, with HRs of 1·50 (1·14-1·98) for high-income countries, 1·80 (1·58-2·06) in middle-income countries, and 2·76 (2·29-3·31) in low-income countries (pinteraction<0·0001). By contrast, we found no or weak associations between wealth and these two outcomes. Differences in outcomes between educational groups were not explained by differences in risk factors, which decreased as the level of education increased in high-income countries, but increased as the level of education increased in low-income countries (pinteraction<0·0001). Medical care (eg, management of hypertension, diabetes, and secondary prevention) seemed to play an important part in adverse cardiovascular disease outcomes because such care is likely to be poorer in people with the lowest levels of education compared to those with higher levels of education in low-income countries; however, we observed less marked differences in care based on level of education in middle-income countries and no or minor differences in high-income countries.

    INTERPRETATION: Although people with a lower level of education in low-income and middle-income countries have higher incidence of and mortality from cardiovascular disease, they have better overall risk factor profiles. However, these individuals have markedly poorer health care. Policies to reduce health inequities globally must include strategies to overcome barriers to care, especially for those with lower levels of education.

    FUNDING: Full funding sources are listed at the end of the paper (see Acknowledgments).

  3. Knox-Brown B, Patel J, Potts J, Ahmed R, Aquart-Stewart A, Cherkaski HH, et al.
    Lancet Glob Health, 2023 Jan;11(1):e69-e82.
    PMID: 36521955 DOI: 10.1016/S2214-109X(22)00456-9
    BACKGROUND: Small airways obstruction is a common feature of obstructive lung diseases. Research is scarce on small airways obstruction, its global prevalence, and risk factors. We aimed to estimate the prevalence of small airways obstruction, examine the associated risk factors, and compare the findings for two different spirometry parameters.

    METHODS: The Burden of Obstructive Lung Disease study is a multinational cross-sectional study of 41 municipalities in 34 countries across all WHO regions. Adults aged 40 years or older who were not living in an institution were eligible to participate. To ensure a representative sample, participants were selected from a random sample of the population according to a predefined site-specific sampling strategy. We included participants' data in this study if they completed the core study questionnaire and had acceptable spirometry according to predefined quality criteria. We excluded participants with a contraindication for lung function testing. We defined small airways obstruction as either mean forced expiratory flow rate between 25% and 75% of the forced vital capacity (FEF25-75) less than the lower limit of normal or forced expiratory volume in 3 s to forced vital capacity ratio (FEV3/FVC ratio) less than the lower limit of normal. We estimated the prevalence of pre-bronchodilator (ie, before administration of 200 μg salbutamol) and post-bronchodilator (ie, after administration of 200 μg salbutamol) small airways obstruction for each site. To identify risk factors for small airways obstruction, we performed multivariable regression analyses within each site and pooled estimates using random-effects meta-analysis.

    FINDINGS: 36 618 participants were recruited between Jan 2, 2003, and Dec 26, 2016. Data were collected from participants at recruitment. Of the recruited participants, 28 604 participants had acceptable spirometry and completed the core study questionnaire. Data were available for 26 443 participants for FEV3/FVC ratio and 25 961 participants for FEF25-75. Of the 26 443 participants included, 12 490 were men and 13 953 were women. Prevalence of pre-bronchodilator small airways obstruction ranged from 5% (34 of 624 participants) in Tartu, Estonia, to 34% (189 of 555 participants) in Mysore, India, for FEF25-75, and for FEV3/FVC ratio it ranged from 5% (31 of 684) in Riyadh, Saudi Arabia, to 31% (287 of 924) in Salzburg, Austria. Prevalence of post-bronchodilator small airways obstruction was universally lower. Risk factors significantly associated with FEV3/FVC ratio less than the lower limit of normal included increasing age, low BMI, active and passive smoking, low level of education, working in a dusty job for more than 10 years, previous tuberculosis, and family history of chronic obstructive pulmonary disease. Results were similar for FEF25-75, except for increasing age, which was associated with reduced odds of small airways obstruction.

    INTERPRETATION: Despite the wide geographical variation, small airways obstruction is common and more prevalent than chronic airflow obstruction worldwide. Small airways obstruction shows the same risk factors as chronic airflow obstruction. However, further research is required to investigate whether small airways obstruction is also associated with respiratory symptoms and lung function decline.

    FUNDING: National Heart and Lung Institute and Wellcome Trust.

    TRANSLATIONS: For the Dutch, Estonian, French, Icelandic, Malay, Marathi, Norwegian, Portuguese, Swedish and Urdu translations of the abstract see Supplementary Materials section.

  4. Shankar PR, Hassali MA, Shahwani NA, Iqbal Q, Anwar M, Saleem F
    Lancet Glob Health, 2016 10;4(10):e689.
    PMID: 27633429 DOI: 10.1016/S2214-109X(16)30214-5
  5. Wegman MP, Altice FL, Kaur S, Rajandaran V, Osornprasop S, Wilson D, et al.
    Lancet Glob Health, 2017 02;5(2):e198-e207.
    PMID: 27964869 DOI: 10.1016/S2214-109X(16)30303-5
    BACKGROUND: Detention of people who use drugs into compulsory drug detention centres (CDDCs) is common throughout East and Southeast Asia. Evidence-based pharmacological therapies for treating substance use disorders, such as opioid agonist treatments with methadone, are generally unavailable in these settings. We used a unique opportunity where CDDCs coexisted with voluntary drug treatment centres (VTCs) providing methadone in Malaysia to compare the timing and occurrence of opioid relapse (measured using urine drug testing) in individuals transitioning from CDDCs versus methadone maintenance in VTCs.

    METHODS: We did a parallel, two-arm, prospective observational study of opioid-dependent individuals aged 18 years and older who were treated in Malaysia in the Klang Valley in two settings: CDDCs and VTCs. We used sequential sampling to recruit individuals. Assessed individuals in CDDCs were required to participate in services such as counselling sessions and manual labour. Assessed individuals in VTCs could voluntarily access many of the components available in CDDCs, in addition to methadone therapy. We undertook urinary drug tests and behavioural interviews to assess individuals at baseline and at 1, 3, 6, 9, and 12 months post-release. The primary outcome was time to opioid relapse post-release in the community confirmed by urinary drug testing in individuals who had undergone baseline interviewing and at least one urine drug test (our analytic sample). Relapse rates between the groups were compared using time-to-event methods. This study is registered at ClinicalTrials.gov (NCT02698098).

    FINDINGS: Between July 17, 2012, and August 21, 2014, we screened 168 CDDC attendees and 113 VTC inpatients; of these, 89 from CDDCs and 95 from VTCs were included in our analytic sample. The baseline characteristics of the two groups were similar. In unadjusted analyses, CDDC participants had significantly more rapid relapse to opioid use post-release compared with VTC participants (median time to relapse 31 days [IQR 26-32] vs 352 days [256-unestimable], log rank test, p<0·0001). VTC participants had an 84% (95% CI 75-90) decreased risk of opioid relapse after adjustment for control variables and inverse propensity of treatment weights. Time-varying effect modelling revealed the largest hazard ratio reduction, at 91% (95% CI 83-96), occurs during the first 50 days in the community.

    INTERPRETATION: Opioid-dependent individuals in CDDCs are significantly more likely to relapse to opioid use after release, and sooner, than those treated with evidence-based treatments such as methadone, suggesting that CDDCs have no role in the treatment of opioid-use disorders.

    FUNDING: The World Bank Group, Doris Duke Charitable Foundation, National Institute on Drug Abuse, Australian National Health & Medical Research Council, National Institute of Mental Health, and the University of Malaya-Malaysian Ministry of Higher Education High Impact Research Grant.

  6. Stephan BCM, Pakpahan E, Siervo M, Licher S, Muniz-Terrera G, Mohan D, et al.
    Lancet Glob Health, 2020 Apr;8(4):e524-e535.
    PMID: 32199121 DOI: 10.1016/S2214-109X(20)30062-0
    BACKGROUND: To date, dementia prediction models have been exclusively developed and tested in high-income countries (HICs). However, most people with dementia live in low-income and middle-income countries (LMICs), where dementia risk prediction research is almost non-existent and the ability of current models to predict dementia is unknown. This study investigated whether dementia prediction models developed in HICs are applicable to LMICs.

    METHODS: Data were from the 10/66 Study. Individuals aged 65 years or older and without dementia at baseline were selected from China, Cuba, the Dominican Republic, Mexico, Peru, Puerto Rico, and Venezuela. Dementia incidence was assessed over 3-5 years, with diagnosis according to the 10/66 Study diagnostic algorithm. Discrimination and calibration were tested for five models: the Cardiovascular Risk Factors, Aging and Dementia risk score (CAIDE); the Study on Aging, Cognition and Dementia (AgeCoDe) model; the Australian National University Alzheimer's Disease Risk Index (ANU-ADRI); the Brief Dementia Screening Indicator (BDSI); and the Rotterdam Study Basic Dementia Risk Model (BDRM). Models were tested with use of Cox regression. The discriminative accuracy of each model was assessed using Harrell's concordance (c)-statistic, with a value of 0·70 or higher considered to indicate acceptable discriminative ability. Calibration (model fit) was assessed statistically using the Grønnesby and Borgan test.

    FINDINGS: 11 143 individuals without baseline dementia and with available follow-up data were included in the analysis. During follow-up (mean 3·8 years [SD 1·3]), 1069 people progressed to dementia across all sites (incidence rate 24·9 cases per 1000 person-years). Performance of the models varied. Across countries, the discriminative ability of the CAIDE (0·52≤c≤0·63) and AgeCoDe (0·57≤c≤0·74) models was poor. By contrast, the ANU-ADRI (0·66≤c≤0·78), BDSI (0·62≤c≤0·78), and BDRM (0·66≤c≤0·78) models showed similar levels of discriminative ability to those of the development cohorts. All models showed good calibration, especially at low and intermediate levels of predicted risk. The models validated best in Peru and poorest in the Dominican Republic and China.

    INTERPRETATION: Not all dementia prediction models developed in HICs can be simply extrapolated to LMICs. Further work defining what number and which combination of risk variables works best for predicting risk of dementia in LMICs is needed. However, models that transport well could be used immediately for dementia prevention research and targeted risk reduction in LMICs.

    FUNDING: National Institute for Health Research, Wellcome Trust, WHO, US Alzheimer's Association, and European Research Council.

  7. Kong YC, Kimman M, Subramaniam S, Yip CH, Jan S, Aung S, et al.
    Lancet Glob Health, 2022 Mar;10(3):e416-e428.
    PMID: 35180423 DOI: 10.1016/S2214-109X(21)00595-7
    BACKGROUND: Complementary medicine, which refers to therapies that are not part of conventional medicine, comprising both evidence-based and non-evidence-based interventions, is increasingly used following a diagnosis of cancer. We aimed to investigate out-of-pocket spending patterns on complementary medicine and its association with adverse financial outcomes following cancer in middle-income countries in southeast Asia.

    METHODS: In this prospective cohort study, data on newly diagnosed patients with cancer were derived from the ASEAN Costs in Oncology (ACTION) cohort study, a prospective longitudinal study in 47 centres located in eight countries in southeast Asia. The ACTION study measured household expenditures on complementary medicine in the immediate year after cancer diagnosis. Participants were given cost diaries at baseline to record illness-related payments that were directly incurred and not reimbursed by insurance over the 12-month period after study recruitment. We assessed incidence of financial catastrophe (out-of-pocket cancer-related costs ≥30% of annual household income), medical impoverishment (reduction in annual household income to below poverty line following subtraction of out-of-pocket cancer-related costs), and economic hardship (inability to make necessary household payments) at 1 year.

    FINDINGS: Between March, 2012, and September, 2013, 9513 participants were recruited into the ACTION cohort study, of whom 4754 (50·0%) participants were included in this analysis. Out-of-pocket expenditures on complementary medicine were reported by 1233 households. These payments constituted 8·6% of the annual total out-of-pocket health costs in lower-middle-income countries and 42·9% in upper-middle-income countries. Expenditures on complementary medicine significantly increased risks of financial catastrophe (adjusted odds ratio 1·52 [95% CI 1·23-1·88]) and medical impoverishment (1·75 [1·36-2·24]) at 12 months in upper-middle-income countries only. However, the risks were significantly higher for economically disadvantaged households, irrespective of country income group.

    INTERPRETATION: Integration of evidence-supported complementary therapies into mainstream cancer care, along with interventions to address use of non-evidence-based complementary medicine, might help alleviate any associated adverse financial impacts.

    FUNDING: None.

  8. Duong M, Islam S, Rangarajan S, Leong D, Kurmi O, Teo K, et al.
    Lancet Glob Health, 2019 05;7(5):e613-e623.
    PMID: 31000131 DOI: 10.1016/S2214-109X(19)30070-1
    BACKGROUND: The associations between the extent of forced expiratory volume in 1 s (FEV1) impairment and mortality, incident cardiovascular disease, and respiratory hospitalisations are unclear, and how these associations might vary across populations is unknown.

    METHODS: In this international, community-based cohort study, we prospectively enrolled adults aged 35-70 years who had no intention of moving residences for 4 years from rural and urban communities across 17 countries. A portable spirometer was used to assess FEV1. FEV1 values were standardised within countries for height, age, and sex, and expressed as a percentage of the country-specific predicted FEV1 value (FEV1%). FEV1% was categorised as no impairment (FEV1% ≥0 SD from country-specific mean), mild impairment (FEV1% <0 SD to -1 SD), moderate impairment (FEV1%

  9. Royston G, Hagar C, Long LA, McMahon D, Pakenham-Walsh N, Wadhwani N, et al.
    Lancet Glob Health, 2015 Jul;3(7):e356-7.
    PMID: 26087979 DOI: 10.1016/S2214-109X(15)00054-6
  10. Local Burden of Disease Household Air Pollution Collaborators
    Lancet Glob Health, 2022 Oct;10(10):e1395-e1411.
    PMID: 36113526 DOI: 10.1016/S2214-109X(22)00332-1
    BACKGROUND: More than 3 billion people do not have access to clean energy and primarily use solid fuels to cook. Use of solid fuels generates household air pollution, which was associated with more than 2 million deaths in 2019. Although local patterns in cooking vary systematically, subnational trends in use of solid fuels have yet to be comprehensively analysed. We estimated the prevalence of solid-fuel use with high spatial resolution to explore subnational inequalities, assess local progress, and assess the effects on health in low-income and middle-income countries (LMICs) without universal access to clean fuels.

    METHODS: We did a geospatial modelling study to map the prevalence of solid-fuel use for cooking at a 5 km × 5 km resolution in 98 LMICs based on 2·1 million household observations of the primary cooking fuel used from 663 population-based household surveys over the years 2000 to 2018. We use observed temporal patterns to forecast household air pollution in 2030 and to assess the probability of attaining the Sustainable Development Goal (SDG) target indicator for clean cooking. We aligned our estimates of household air pollution to geospatial estimates of ambient air pollution to establish the risk transition occurring in LMICs. Finally, we quantified the effect of residual primary solid-fuel use for cooking on child health by doing a counterfactual risk assessment to estimate the proportion of deaths from lower respiratory tract infections in children younger than 5 years that could be associated with household air pollution.

    FINDINGS: Although primary reliance on solid-fuel use for cooking has declined globally, it remains widespread. 593 million people live in districts where the prevalence of solid-fuel use for cooking exceeds 95%. 66% of people in LMICs live in districts that are not on track to meet the SDG target for universal access to clean energy by 2030. Household air pollution continues to be a major contributor to particulate exposure in LMICs, and rising ambient air pollution is undermining potential gains from reductions in the prevalence of solid-fuel use for cooking in many countries. We estimated that, in 2018, 205 000 (95% uncertainty interval 147 000-257 000) children younger than 5 years died from lower respiratory tract infections that could be attributed to household air pollution.

    INTERPRETATION: Efforts to accelerate the adoption of clean cooking fuels need to be substantially increased and recalibrated to account for subnational inequalities, because there are substantial opportunities to improve air quality and avert child mortality associated with household air pollution.

    FUNDING: Bill & Melinda Gates Foundation.

  11. Narasimhan M, Pillay Y, García PJ, Allotey P, Gorna R, Welbourn A, et al.
    Lancet Glob Health, 2018 10;6(10):e1058-e1059.
    PMID: 30031731 DOI: 10.1016/S2214-109X(18)30316-4
  12. Murphy A, Palafox B, O'Donnell O, Stuckler D, Perel P, AlHabib KF, et al.
    Lancet Glob Health, 2018 Mar;6(3):e292-e301.
    PMID: 29433667 DOI: 10.1016/S2214-109X(18)30031-7
    BACKGROUND: There is little evidence on the use of secondary prevention medicines for cardiovascular disease by socioeconomic groups in countries at different levels of economic development.

    METHODS: We assessed use of antiplatelet, cholesterol, and blood-pressure-lowering drugs in 8492 individuals with self-reported cardiovascular disease from 21 countries enrolled in the Prospective Urban Rural Epidemiology (PURE) study. Defining one or more drugs as a minimal level of secondary prevention, wealth-related inequality was measured using the Wagstaff concentration index, scaled from -1 (pro-poor) to 1 (pro-rich), standardised by age and sex. Correlations between inequalities and national health-related indicators were estimated.

    FINDINGS: The proportion of patients with cardiovascular disease on three medications ranged from 0% in South Africa (95% CI 0-1·7), Tanzania (0-3·6), and Zimbabwe (0-5·1), to 49·3% in Canada (44·4-54·3). Proportions receiving at least one drug varied from 2·0% (95% CI 0·5-6·9) in Tanzania to 91·4% (86·6-94·6) in Sweden. There was significant (p<0·05) pro-rich inequality in Saudi Arabia, China, Colombia, India, Pakistan, and Zimbabwe. Pro-poor distributions were observed in Sweden, Brazil, Chile, Poland, and the occupied Palestinian territory. The strongest predictors of inequality were public expenditure on health and overall use of secondary prevention medicines.

    INTERPRETATION: Use of medication for secondary prevention of cardiovascular disease is alarmingly low. In many countries with the lowest use, pro-rich inequality is greatest. Policies associated with an equal or pro-poor distribution include free medications and community health programmes to support adherence to medications.

    FUNDING: Full funding sources listed at the end of the paper (see Acknowledgments).

  13. Dokainish H, Teo K, Zhu J, Roy A, AlHabib KF, ElSayed A, et al.
    Lancet Glob Health, 2017 07;5(7):e665-e672.
    PMID: 28476564 DOI: 10.1016/S2214-109X(17)30196-1
    BACKGROUND: Most data on mortality and prognostic factors in patients with heart failure come from North America and Europe, with little information from other regions. Here, in the International Congestive Heart Failure (INTER-CHF) study, we aimed to measure mortality at 1 year in patients with heart failure in Africa, China, India, the Middle East, southeast Asia and South America; we also explored demographic, clinical, and socioeconomic variables associated with mortality.

    METHODS: We enrolled consecutive patients with heart failure (3695 [66%] clinic outpatients, 2105 [34%] hospital in patients) from 108 centres in six geographical regions. We recorded baseline demographic and clinical characteristics and followed up patients at 6 months and 1 year from enrolment to record symptoms, medications, and outcomes. Time to death was studied with Cox proportional hazards models adjusted for demographic and clinical variables, medications, socioeconomic variables, and region. We used the explained risk statistic to calculate the relative contribution of each level of adjustment to the risk of death.

    FINDINGS: We enrolled 5823 patients within 1 year (with 98% follow-up). Overall mortality was 16·5%: highest in Africa (34%) and India (23%), intermediate in southeast Asia (15%), and lowest in China (7%), South America (9%), and the Middle East (9%). Regional differences persisted after multivariable adjustment. Independent predictors of mortality included cardiac variables (New York Heart Association Functional Class III or IV, previous admission for heart failure, and valve disease) and non-cardiac variables (body-mass index, chronic kidney disease, and chronic obstructive pulmonary disease). 46% of mortality risk was explained by multivariable modelling with these variables; however, the remainder was unexplained.

    INTERPRETATION: Marked regional differences in mortality in patients with heart failure persisted after multivariable adjustment for cardiac and non-cardiac factors. Therefore, variations in mortality between regions could be the result of health-care infrastructure, quality and access, or environmental and genetic factors. Further studies in large, global cohorts are needed.

    FUNDING: The study was supported by Novartis.

    Study site: Multination
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