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Naghavi M, Ong KL, Aali A, Ababneh HS, Abate YH, Abbafati C, Abbasgholizadeh R, Abbasian M, Abbasi-Kangevari M, Abbastabar H, Abd ElHafeez S, Abdelmasseh M, Abd-Elsalam S, Abdelwahab A, Abdollahi M, Abdollahifar MA, Abdoun M, Abdulah DM, Abdullahi A, Abebe M, Abebe SS, Abedi A, Abegaz KH, Abhilash ES, Abidi H, Abiodun O, Aboagye RG, Abolhassani H, Abolmaali M, Abouzid M, Aboye GB, Abreu LG, Abrha WA, Abtahi D, Abu Rumeileh S, Abualruz H, Abubakar B, Abu-Gharbieh E, Abu-Rmeileh NME, Aburuz S, Abu-Zaid A, Accrombessi MMK, Adal TG, Adamu AA, Addo IY, Addolorato G, Adebiyi AO, Adekanmbi V, Adepoju AV, Adetunji CO, Adetunji JB, Adeyeoluwa TE, Adeyinka DA, Adeyomoye OI, Admass BAA, Adnani QES, Adra S, Afolabi AA, Afzal MS, Afzal S, Agampodi SB, Agasthi P, Aggarwal M, Aghamiri S, Agide FD, Agodi A, Agrawal A, Agyemang-Duah W, Ahinkorah BO, Ahmad A, Ahmad D, Ahmad F, Ahmad MM, Ahmad S, Ahmad S, Ahmad T, Ahmadi K, Ahmadzade AM, Ahmed A, Ahmed A, Ahmed H, Ahmed LA, Ahmed MS, Ahmed MS, Ahmed MB, 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K, Deng X, Denova-Gutiérrez E, Deravi N, Dereje N, Dervenis N, Dervišević E, Des Jarlais DC, Desai HD, Desai R, Devanbu VGC, Dewan SMR, Dhali A, Dhama K, Dhimal M, Dhingra S, Dhulipala VR, Dias da Silva D, Diaz D, Diaz MJ, Dima A, Ding DD, Ding H, Dinis-Oliveira RJ, Dirac MA, Djalalinia S, Do THP, do Prado CB, Doaei S, Dodangeh M, Dodangeh M, Dohare S, Dokova KG, Dolecek C, Dominguez RMV, Dong W, Dongarwar D, D'Oria M, Dorostkar F, Dorsey ER, dos Santos WM, Doshi R, Doshmangir L, Dowou RK, Driscoll TR, Dsouza HL, Dsouza V, Du M, Dube J, Duncan BB, Duraes AR, Duraisamy S, Durojaiye OC, Dwyer-Lindgren L, Dzianach PA, Dziedzic AM, E'mar AR, Eboreime E, Ebrahimi A, Echieh CP, Edinur HA, Edvardsson D, Edvardsson K, Efendi D, Efendi F, Effendi DE, Eikemo TA, Eini E, Ekholuenetale M, Ekundayo TC, El Sayed I, Elbarazi I, Elema TB, Elemam NM, Elgar FJ, Elgendy IY, ElGohary GMT, Elhabashy HR, Elhadi M, El-Huneidi W, Elilo LT, Elmeligy OAA, Elmonem MA, Elshaer M, Elsohaby I, Emeto TI, Engelbert 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Ghahramani S, Ghailan KY, Ghasemi MR, Ghasempour Dabaghi G, Ghasemzadeh A, Ghashghaee A, Ghassemi F, Ghazy RM, Ghimire A, Ghoba S, Gholamalizadeh M, Gholamian A, Gholamrezanezhad A, Gholizadeh N, Ghorbani M, Ghorbani Vajargah P, Ghoshal AG, Gill PS, Gill TK, Gillum RF, Ginindza TG, Girmay A, Glasbey JC, Gnedovskaya EV, Göbölös L, Godinho MA, Goel A, Golchin A, Goldust M, Golechha M, Goleij P, Gomes NGM, Gona PN, Gopalani SV, Gorini G, Goudarzi H, Goulart AC, Goulart BNG, Goyal A, Grada A, Graham SM, Grivna M, Grosso G, Guan SY, Guarducci G, Gubari MIM, Gudeta MD, Guha A, Guicciardi S, Guimarães RA, Gulati S, Gunawardane DA, Gunturu S, Guo C, Gupta AK, Gupta B, Gupta MK, Gupta M, Gupta RD, Gupta R, Gupta S, Gupta VB, Gupta VK, Gupta VK, Gurmessa L, Gutiérrez RA, Habibzadeh F, Habibzadeh P, Haddadi R, Hadei M, Hadi NR, Haep N, Hafezi-Nejad N, Hailu A, Haj-Mirzaian A, Halboub ES, Hall BJ, Haller S, Halwani R, Hamadeh RR, Hameed S, Hamidi S, Hamilton EB, Han C, Han Q, Hanif A, Hanifi N, 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A, Lai DTC, Lal DK, Lalloo R, Lallukka T, Lam H, Lám J, Landrum KR, Lanfranchi F, Lang JJ, Langguth B, Lansingh VC, Laplante-Lévesque A, Larijani B, Larsson AO, Lasrado S, Lassi ZS, Latief K, Latifinaibin K, Lauriola P, Le NHH, Le TTT, Le TDT, Ledda C, Ledesma JR, Lee M, Lee PH, Lee SW, Lee SWH, Lee WC, Lee YH, LeGrand KE, Leigh J, Leong E, Lerango TL, Li MC, Li W, Li X, Li Y, Li Z, Ligade VS, Likaka ATM, Lim LL, Lim SS, Lindstrom M, Linehan C, Liu C, Liu G, Liu J, Liu R, Liu S, Liu X, Liu X, Llanaj E, Loftus MJ, López-Bueno R, Lopukhov PD, Loreche AM, Lorkowski S, Lotufo PA, Lozano R, Lubinda J, Lucchetti G, Lugo A, Lunevicius R, Ma ZF, Maass KL, Machairas N, Machoy M, Madadizadeh F, Madsen C, Madureira-Carvalho ÁM, Maghazachi AA, Maharaj SB, Mahjoub S, Mahmoud MA, Mahmoudi A, Mahmoudi E, Mahmoudi R, Majeed A, Makhdoom IF, Malakan Rad E, Maled V, Malekzadeh R, Malhotra AK, Malhotra K, Malik AA, Malik I, Malta DC, Mamun AA, Mansouri P, Mansournia MA, Mantovani LG, Maqsood S, Marasini 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Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet 2024; 403:2100-2132. [PMID: 38582094 DOI: 10.1016/s0140-6736(24)00367-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 02/15/2024] [Accepted: 02/22/2024] [Indexed: 04/08/2024]
Abstract
BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation.
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Burden of disease scenarios for 204 countries and territories, 2022-2050: a forecasting analysis for the Global Burden of Disease Study 2021. Lancet 2024; 403:2204-2256. [PMID: 38762325 DOI: 10.1016/s0140-6736(24)00685-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 03/29/2024] [Accepted: 04/02/2024] [Indexed: 05/20/2024]
Abstract
BACKGROUND Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. METHODS Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. FINDINGS In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8-63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0-45·0] in 2050) and south Asia (31·7% [29·2-34·1] to 15·5% [13·7-17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4-40·3) to 41·1% (33·9-48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6-25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5-43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5-17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7-11·3) in the high-income super-region to 23·9% (20·7-27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5-6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2-26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [-0·6 to 3·6]). INTERPRETATION Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions. FUNDING Bill & Melinda Gates Foundation.
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MZ, Yousefi Z, Yu C, Yu Y, Yuan CW, Zafari N, Zakham F, Zaki N, Zamagni G, Zandi M, Zandieh GGZ, Zangiabadian M, Zastrozhin MS, Zhang H, Zhang M, Zhang Y, Zhong C, Zhou J, Zhu B, Zhu L, Zielińska M, Zou Z, Zyoud SH, Murray CJL, Smith AE, Vollset SE. Global fertility in 204 countries and territories, 1950-2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021. Lancet 2024; 403:2057-2099. [PMID: 38521087 PMCID: PMC11122687 DOI: 10.1016/s0140-6736(24)00550-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 12/28/2023] [Accepted: 03/15/2024] [Indexed: 03/25/2024]
Abstract
BACKGROUND Accurate assessments of current and future fertility-including overall trends and changing population age structures across countries and regions-are essential to help plan for the profound social, economic, environmental, and geopolitical challenges that these changes will bring. Estimates and projections of fertility are necessary to inform policies involving resource and health-care needs, labour supply, education, gender equality, and family planning and support. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 produced up-to-date and comprehensive demographic assessments of key fertility indicators at global, regional, and national levels from 1950 to 2021 and forecast fertility metrics to 2100 based on a reference scenario and key policy-dependent alternative scenarios. METHODS To estimate fertility indicators from 1950 to 2021, mixed-effects regression models and spatiotemporal Gaussian process regression were used to synthesise data from 8709 country-years of vital and sample registrations, 1455 surveys and censuses, and 150 other sources, and to generate age-specific fertility rates (ASFRs) for 5-year age groups from age 10 years to 54 years. ASFRs were summed across age groups to produce estimates of total fertility rate (TFR). Livebirths were calculated by multiplying ASFR and age-specific female population, then summing across ages 10-54 years. To forecast future fertility up to 2100, our Institute for Health Metrics and Evaluation (IHME) forecasting model was based on projections of completed cohort fertility at age 50 years (CCF50; the average number of children born over time to females from a specified birth cohort), which yields more stable and accurate measures of fertility than directly modelling TFR. CCF50 was modelled using an ensemble approach in which three sub-models (with two, three, and four covariates variously consisting of female educational attainment, contraceptive met need, population density in habitable areas, and under-5 mortality) were given equal weights, and analyses were conducted utilising the MR-BRT (meta-regression-Bayesian, regularised, trimmed) tool. To capture time-series trends in CCF50 not explained by these covariates, we used a first-order autoregressive model on the residual term. CCF50 as a proportion of each 5-year ASFR was predicted using a linear mixed-effects model with fixed-effects covariates (female educational attainment and contraceptive met need) and random intercepts for geographical regions. Projected TFRs were then computed for each calendar year as the sum of single-year ASFRs across age groups. The reference forecast is our estimate of the most likely fertility future given the model, past fertility, forecasts of covariates, and historical relationships between covariates and fertility. We additionally produced forecasts for multiple alternative scenarios in each location: the UN Sustainable Development Goal (SDG) for education is achieved by 2030; the contraceptive met need SDG is achieved by 2030; pro-natal policies are enacted to create supportive environments for those who give birth; and the previous three scenarios combined. Uncertainty from past data inputs and model estimation was propagated throughout analyses by taking 1000 draws for past and present fertility estimates and 500 draws for future forecasts from the estimated distribution for each metric, with 95% uncertainty intervals (UIs) given as the 2·5 and 97·5 percentiles of the draws. To evaluate the forecasting performance of our model and others, we computed skill values-a metric assessing gain in forecasting accuracy-by comparing predicted versus observed ASFRs from the past 15 years (2007-21). A positive skill metric indicates that the model being evaluated performs better than the baseline model (here, a simplified model holding 2007 values constant in the future), and a negative metric indicates that the evaluated model performs worse than baseline. FINDINGS During the period from 1950 to 2021, global TFR more than halved, from 4·84 (95% UI 4·63-5·06) to 2·23 (2·09-2·38). Global annual livebirths peaked in 2016 at 142 million (95% UI 137-147), declining to 129 million (121-138) in 2021. Fertility rates declined in all countries and territories since 1950, with TFR remaining above 2·1-canonically considered replacement-level fertility-in 94 (46·1%) countries and territories in 2021. This included 44 of 46 countries in sub-Saharan Africa, which was the super-region with the largest share of livebirths in 2021 (29·2% [28·7-29·6]). 47 countries and territories in which lowest estimated fertility between 1950 and 2021 was below replacement experienced one or more subsequent years with higher fertility; only three of these locations rebounded above replacement levels. Future fertility rates were projected to continue to decline worldwide, reaching a global TFR of 1·83 (1·59-2·08) in 2050 and 1·59 (1·25-1·96) in 2100 under the reference scenario. The number of countries and territories with fertility rates remaining above replacement was forecast to be 49 (24·0%) in 2050 and only six (2·9%) in 2100, with three of these six countries included in the 2021 World Bank-defined low-income group, all located in the GBD super-region of sub-Saharan Africa. The proportion of livebirths occurring in sub-Saharan Africa was forecast to increase to more than half of the world's livebirths in 2100, to 41·3% (39·6-43·1) in 2050 and 54·3% (47·1-59·5) in 2100. The share of livebirths was projected to decline between 2021 and 2100 in most of the six other super-regions-decreasing, for example, in south Asia from 24·8% (23·7-25·8) in 2021 to 16·7% (14·3-19·1) in 2050 and 7·1% (4·4-10·1) in 2100-but was forecast to increase modestly in the north Africa and Middle East and high-income super-regions. Forecast estimates for the alternative combined scenario suggest that meeting SDG targets for education and contraceptive met need, as well as implementing pro-natal policies, would result in global TFRs of 1·65 (1·40-1·92) in 2050 and 1·62 (1·35-1·95) in 2100. The forecasting skill metric values for the IHME model were positive across all age groups, indicating that the model is better than the constant prediction. INTERPRETATION Fertility is declining globally, with rates in more than half of all countries and territories in 2021 below replacement level. Trends since 2000 show considerable heterogeneity in the steepness of declines, and only a small number of countries experienced even a slight fertility rebound after their lowest observed rate, with none reaching replacement level. Additionally, the distribution of livebirths across the globe is shifting, with a greater proportion occurring in the lowest-income countries. Future fertility rates will continue to decline worldwide and will remain low even under successful implementation of pro-natal policies. These changes will have far-reaching economic and societal consequences due to ageing populations and declining workforces in higher-income countries, combined with an increasing share of livebirths among the already poorest regions of the world. FUNDING Bill & Melinda Gates Foundation.
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Solaimanian S, Solanki R, Solanki S, Soliman SSM, Somayaji R, Song Y, Sorensen RJD, Soriano JB, Soyiri IN, Spartalis M, Spearman S, Spencer CN, Sreeramareddy CT, Stachteas P, Stafford LK, Stanaway JD, Stanikzai MH, Stein C, Stein DJ, Steinbeis F, Steiner C, Steinke S, Steiropoulos P, Stockfelt L, Stokes MA, Straif K, Stranges S, Subedi N, Subramaniyan V, Suleman M, Suliankatchi Abdulkader R, Sundström J, Sunkersing D, Sunnerhagen KS, Suresh V, Swain CK, Szarpak L, Szeto MD, Tabaee Damavandi P, Tabarés-Seisdedos R, Tabatabaei SM, Tabatabaei Malazy O, Tabatabaeizadeh SA, Tabatabai S, Tabche C, Tabish M, Tadakamadla SK, Taheri Abkenar Y, Taheri Soodejani M, Taherkhani A, Taiba J, Takahashi K, Talaat IM, Tamuzi JL, Tan KK, Tang H, Tat NY, Taveira N, Tefera YM, Tehrani-Banihashemi A, Temesgen WA, Temsah MH, Teramoto M, Terefa DR, Teye-Kwadjo E, Thakur R, Thangaraju P, Thankappan KR, Thapar R, Thayakaran R, Thirunavukkarasu S, Thomas N, Thomas NK, Tian J, Tichopad A, Ticoalu JHV, Tiruye TY, Tobe-Gai R, Tolani MA, Tolossa T, Tonelli M, Topor-Madry R, Topouzis F, Touvier M, Tovani-Palone MR, Trabelsi K, Tran JT, Tran MTN, Tran NM, Trico D, Trihandini I, Troeger CE, Tromans SJ, Truyen TTTT, Tsatsakis A, Tsermpini EE, Tumurkhuu M, Udoakang AJ, Udoh A, Ullah A, Ullah S, Ullah S, Umair M, Umakanthan S, Unim B, Unnikrishnan B, Upadhyay E, Urso D, Usman JS, Vaithinathan AG, Vakili O, Valenti M, Valizadeh R, Van den Eynde J, van Donkelaar A, Varga O, Vart P, Varthya SB, Vasankari TJ, Vasic M, Vaziri S, Venketasubramanian N, Verghese NA, Verma M, Veroux M, Verras GI, Vervoort D, Villafañe JH, Villalobos-Daniel VE, Villani L, Villanueva GI, Vinayak M, Violante FS, Vlassov V, Vo B, Vollset SE, Volovat SR, Vos T, Vujcic IS, Waheed Y, Wang C, Wang F, Wang S, Wang Y, Wang YP, Wanjau MN, Waqas M, Ward P, Waris A, Wassie EG, Weerakoon KG, Weintraub RG, Weiss DJ, Weiss EJ, Weldetinsaa HLL, Wells KM, Wen YF, Wiangkham T, Wickramasinghe ND, Wilkerson C, Willeit P, Wilson S, Wong YJ, Wongsin U, Wozniak S, Wu C, Wu D, Wu F, Wu Z, Xia J, Xiao H, Xu S, Xu X, Xu YY, Yadav MK, Yaghoubi S, Yamagishi K, Yang L, Yano Y, Yaribeygi H, Yasufuku Y, Ye P, Yesodharan R, Yesuf SA, Yezli S, Yi S, Yiğit A, Yigzaw ZA, Yin D, Yip P, Yismaw MB, Yon DK, Yonemoto N, You Y, Younis MZ, Yousefi Z, Yu C, Yu Y, Zadey S, Zadnik V, Zakham F, Zaki N, Zakzuk J, Zamagni G, Zaman SB, Zandieh GGZ, Zanghì A, Zar HJ, Zare I, Zarimeidani F, Zastrozhin MS, Zeng Y, Zhai C, Zhang AL, Zhang H, Zhang L, Zhang M, Zhang Y, Zhang Z, Zhang ZJ, Zhao H, Zhao JT, Zhao XJG, Zhao Y, Zhao Y, Zhong C, Zhou J, Zhou J, Zhou S, Zhu B, Zhu L, Zhu Z, Ziaeian B, Ziafati M, Zielińska M, Zimsen SRM, Zoghi G, Zoller T, Zumla A, Zyoud SH, Zyoud SH, Murray CJL, Gakidou E. Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet 2024; 403:2162-2203. [PMID: 38762324 DOI: 10.1016/s0140-6736(24)00933-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 03/11/2024] [Accepted: 05/02/2024] [Indexed: 05/20/2024]
Abstract
BACKGROUND Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. METHODS The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk-outcome pairs. Pairs were included on the basis of data-driven determination of a risk-outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk-outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk-outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. FINDINGS Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7-9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4-9·2]), smoking (5·7% [4·7-6·8]), low birthweight and short gestation (5·6% [4·8-6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8-6·0]). For younger demographics (ie, those aged 0-4 years and 5-14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9-27·7]) and environmental and occupational risks (decrease of 22·0% [15·5-28·8]), coupled with a 49·4% (42·3-56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9-21·7] for high BMI and 7·9% [3·3-12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6-1·9) for high BMI and 1·3% (1·1-1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4-78·8) for child growth failure and 66·3% (60·2-72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). INTERPRETATION Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions. FUNDING Bill & Melinda Gates Foundation.
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Ramazanu S, Rana J, Rana K, Ranabhat CL, Rancic N, Rani S, Ranjan S, Rao CR, Rao IR, Rao M, Rao SJ, Rasali DP, Rasella D, Rashedi S, Rashedi V, Rashid AM, Rasouli-Saravani A, Rastogi P, Rasul A, Ravangard R, Ravikumar N, Rawaf DL, Rawaf S, Rawassizadeh R, Razeghian-Jahromi I, Reddy MMRK, Redwan EMM, Rehman FU, Reiner Jr RC, Remuzzi G, Reshmi B, Resnikoff S, Reyes LF, Rezaee M, Rezaei N, Rezaei N, Rezaeian M, Riaz MA, Ribeiro AI, Ribeiro DC, Rickard J, Rios-Blancas MJ, Robinson-Oden HE, Rodrigues M, Rodriguez JAB, Roever L, Rohilla R, Rohloff P, Romadlon DS, Ronfani L, Roshandel G, Roshanzamir S, Rostamian M, Roy B, Roy P, Rubagotti E, Rumisha SF, Rwegerera GM, Rynkiewicz A, S M, S N C, S Sunnerhagen K, Saad AMA, Sabbatucci M, Saber K, Saber-Ayad MM, Sacco S, Saddik B, Saddler A, Sadee BA, Sadeghi E, Sadeghi M, Sadeghian S, Saeed U, Saeedi M, Safi S, Sagar R, Saghazadeh A, Saheb Sharif-Askari N, Sahoo SS, Sahraian MA, Sajedi SA, Sajid MR, Sakshaug JW, Salahi S, Salahi S, Salamati P, Salami AA, Salaroli LB, Saleh MA, Salehi S, Salem MR, Salem MZY, Salimi S, Samadi Kafil H, Samadzadeh S, Samara KA, Samargandy S, Samodra YL, Samuel VP, Samy AM, Sanabria J, Sanadgol N, Sanganyado E, Sanjeev RK, Sanmarchi F, Sanna F, Santri IN, Santric-Milicevic MM, Sarasmita MA, Saravanan A, Saravi B, Sarikhani Y, Sarkar C, Sarmiento-Suárez R, Sarode GS, Sarode SC, Sarveazad A, Sathian B, Sathish T, Sattin D, Saulam J, Sawyer SM, Saxena S, Saya GK, Sayadi Y, Sayeed A, Sayeed MA, Saylan M, Scarmeas N, Schaarschmidt BM, Schlee W, Schmidt MI, Schuermans A, Schwebel DC, Schwendicke F, Šekerija M, Selvaraj S, Semreen MH, Senapati S, Sengupta P, Senthilkumaran S, Sepanlou SG, Serban D, Sertsu A, Sethi Y, SeyedAlinaghi S, Seyedi SA, Shafaat A, Shafaat O, Shafie M, Shafiee A, Shah NS, Shah PA, Shahabi S, Shahbandi A, Shahid I, Shahid S, Shahid W, Shahwan MJ, Shaikh MA, Shakeri A, Shakil H, Sham S, Shamim MA, Shams-Beyranvand M, Shamshad H, Shamshirgaran MA, Shamsi MA, Shanawaz M, Shankar A, Sharfaei S, Sharifan A, Shariff M, Sharifi-Rad J, Sharma M, Sharma R, Sharma S, Sharma V, Shastry RP, Shavandi A, Shaw DH, Shayan AM, Shehabeldine AME, Sheikh A, Sheikhi RA, Shen J, Shenoy MM, Shetty BSK, Shetty RS, Shey RA, Shiani A, Shibuya K, Shiferaw D, Shigematsu M, Shin JI, Shin MJ, Shiri R, Shirkoohi R, Shittu A, Shiue I, Shivakumar KM, Shivarov V, Shool S, Shrestha S, Shuja KH, Shuval K, Si Y, Sibhat MM, Siddig EE, Sigfusdottir ID, Silva JP, Silva LMLR, Silva S, Simões JP, Simpson CR, Singal A, Singh A, Singh A, Singh A, Singh BB, Singh B, Singh M, Singh M, Singh NP, Singh P, Singh S, Siraj MS, Sitas F, Sivakumar S, Skryabin VY, Skryabina AA, Sleet DA, Slepak ELN, Sohrabi H, Soleimani H, Soliman SSM, Solmi M, Solomon Y, Song Y, Sorensen RJD, Soriano JB, Soyiri IN, Spartalis M, Sreeramareddy CT, Starnes JR, Starodubov VI, Starodubova AV, Stefan SC, Stein DJ, Steinbeis F, Steiropoulos P, Stockfelt L, Stokes MA, Stortecky S, Stranges S, Stroumpoulis K, Suleman M, Suliankatchi Abdulkader R, Sultana A, Sun J, Sunkersing D, Susanty S, Swain CK, Sykes BL, Szarpak L, Szeto MD, Szócska M, Tabaee Damavandi P, Tabatabaei Malazy O, Tabatabaeizadeh SA, Tabatabai S, Tabb KM, Tabish M, Taborda-Barata LM, Tabuchi T, Tadesse BT, Taheri A, Taheri Abkenar Y, Taheri Soodejani M, Taherkhani A, Taiba J, Tajbakhsh A, Talaat IM, Talukder A, Tamuzi JL, Tan KK, Tang H, Tang HK, Tat NY, Tat VY, Tavakoli Oliaee R, Tavangar SM, Taveira N, Tebeje TM, Tefera YM, Teimoori M, Temsah MH, Temsah RMH, Teramoto M, Tesfaye SH, Thangaraju P, Thankappan KR, Thapa R, Thapar R, Thomas N, Thrift AG, Thum CCC, Tian J, Tichopad A, Ticoalu JHV, Tiruye TY, Tohidast SA, Tonelli M, Touvier M, Tovani-Palone MR, Tram KH, Tran NM, Trico D, Trihandini I, Tromans SJ, Truong VT, Truyen TTTT, Tsermpini EE, Tumurkhuu M, Tung K, Tyrovolas S, Ubah CS, Udoakang AJ, Udoh A, Ulhaq I, Ullah S, Ullah S, Umair M, Umar TP, Umeokonkwo CD, Umesh A, Unim B, Unnikrishnan B, Upadhyay E, Urso D, Vacante M, Vahdani AM, Vaithinathan AG, Valadan Tahbaz S, Valizadeh R, Van den Eynde J, Varavikova E, Varga O, Varma SA, Vart P, Varthya SB, Vasankari TJ, Veerman LJ, Venketasubramanian N, Venugopal D, Verghese NA, Verma M, Verma P, Veroux M, Verras GI, Vervoort D, Vieira RJ, Villafañe JH, Villani L, Villanueva GI, Villeneuve PJ, Violante FS, Visontay R, Vlassov V, Vo B, Vollset SE, Volovat SR, Volovici V, Vongpradith A, Vos T, Vujcic IS, Vukovic R, Wado YD, Wafa HA, Waheed Y, Wamai RG, Wang C, Wang D, Wang F, Wang S, Wang S, Wang Y, Wang YP, Ward P, Watson S, Weaver MR, Weerakoon KG, Weiss DJ, Weldemariam AH, Wells KM, Wen YF, Werdecker A, Westerman R, Wickramasinghe DP, Wickramasinghe ND, Wijeratne T, Wilson S, Wojewodzic MW, Wool EE, Woolf AD, Wu D, Wulandari RD, Xiao H, Xu B, Xu X, Yadav L, Yaghoubi S, Yang L, Yano Y, Yao Y, Ye P, Yesera GE, Yesodharan R, Yesuf SA, Yiğit A, Yiğit V, Yip P, Yon DK, Yonemoto N, You Y, Younis MZ, Yu C, Zadey S, Zadnik V, Zafari N, Zahedi M, Zahid MN, Zahir M, Zakham F, Zaki N, Zakzuk J, Zamagni G, Zaman BA, Zaman SB, Zamora N, Zand R, Zandi M, Zandieh GGZ, Zanghì A, Zare I, Zastrozhin MS, Zeariya MGM, Zeng Y, Zhai C, Zhang C, Zhang H, Zhang H, Zhang Y, Zhang Z, Zhang Z, Zhao H, Zhao Y, Zhao Y, Zheng P, Zhong C, Zhou J, Zhu B, Zhu Z, Ziaeefar P, Zielińska M, Zou Z, Zumla A, Zweck E, Zyoud SH, Lim SS, Murray CJL. Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950-2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021. Lancet 2024; 403:1989-2056. [PMID: 38484753 DOI: 10.1016/s0140-6736(24)00476-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 12/08/2023] [Accepted: 03/06/2024] [Indexed: 04/13/2024]
Abstract
BACKGROUND Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020-21 COVID-19 pandemic period. METHODS 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. FINDINGS Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5-65·1] decline), and increased during the COVID-19 pandemic period (2020-21; 5·1% [0·9-9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98-5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50-6·01) in 2019. An estimated 131 million (126-137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7-17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8-24·8), from 49·0 years (46·7-51·3) to 71·7 years (70·9-72·5). Global life expectancy at birth declined by 1·6 years (1·0-2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67-8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4-52·7]) and south Asia (26·3% [9·0-44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. INTERPRETATION Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic. FUNDING Bill & Melinda Gates Foundation.
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Kanmiki EW, Mamun AA, Phillips JF, O'Flaherty MJ. Effect of a community-based primary healthcare programme on adverse pregnancy outcomes in Northern Ghana. Int J Health Plann Manage 2024; 39:329-342. [PMID: 37922332 DOI: 10.1002/hpm.3730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Revised: 10/20/2023] [Accepted: 10/22/2023] [Indexed: 11/05/2023] Open
Abstract
BACKGROUND Pregnancy complications and adverse birth outcomes are among the major contributors to poor maternal and child health. Mothers in remote communities are at higher risk of adverse birth outcomes due to constraints in access to healthcare services. In Ghana, a community-based primary healthcare programme called the Ghana Essential Health Interventions Programme (GEHIP) was implemented in a rural region to help strengthen primary healthcare delivery and improve maternal and child healthcare services delivery. This study assessed the effect of this programme on adverse pregnancy outcomes. METHODS Baseline and end-line survey data from reproductive-aged women from the GEHIP project were used in this analysis. Difference-in-differences and logistic regressions were used to examine the impact and equity effect of GEHIP on adverse pregnancy outcomes using household wealth index and maternal educational attainment as equity measures. The analysis involves the comparison of project baseline and end-line outcomes in intervention and non-intervention districts. RESULTS The intervention had a significant effect in the reduction of adverse pregnancy outcomes (OR = 0.96, 95% CI:0.93-0.99). Although disadvantaged groups experience larger reductions in adverse pregnancy outcomes, controlling for covariates, there was no statistically significant equity effect of GEHIP on adverse pregnancy outcomes using either the household wealth index (OR = 0.99, 95% CI:0.85-1.16) or maternal educational attainment (OR = 0.68, 95% CI: 0.44-1.07) as equity measures. CONCLUSION GEHIP's community-based healthcare programme reduced adverse pregnancy outcomes but no effect on relative equity was established. Factoring in approaches for targeting disadvantaged populations in the implementation of community-based health programs is crucial to ensuring equity in health outcomes.
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Affiliation(s)
- Edmund Wedam Kanmiki
- Institute for Social Science Research, The University of Queensland, Indooroopilly, Queensland, Australia
- Poche Centre for Indigenous Health, Faculty of Health and Behavioural Science, The University of Queensland, Saint Lucia, Queensland, Australia
- ARC Centre of Excellence for Children and Families Over the Life Course (The Life Course Centre), The University of Queensland, Indooroopilly, Queensland, Australia
| | - Abdullah A Mamun
- Poche Centre for Indigenous Health, Faculty of Health and Behavioural Science, The University of Queensland, Saint Lucia, Queensland, Australia
- ARC Centre of Excellence for Children and Families Over the Life Course (The Life Course Centre), The University of Queensland, Indooroopilly, Queensland, Australia
| | - James F Phillips
- Heilbrunn Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York, New York, USA
| | - Martin J O'Flaherty
- Institute for Social Science Research, The University of Queensland, Indooroopilly, Queensland, Australia
- ARC Centre of Excellence for Children and Families Over the Life Course (The Life Course Centre), The University of Queensland, Indooroopilly, Queensland, Australia
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Mamun AA, Kanmiki EW, Leske S, Stajic J, Ward J. Research needed on urban Indigenous health inequalities. Bull World Health Organ 2024; 102:146-148. [PMID: 38313144 PMCID: PMC10835635 DOI: 10.2471/blt.23.290868] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 12/14/2023] [Accepted: 12/15/2023] [Indexed: 02/06/2024] Open
Affiliation(s)
- Abdullah A Mamun
- UQ Poche Centre for Indigenous Health, The University of Queensland, Brisbane, 74 High Street Toowong, Queensland, 4066, Australia
| | - Edmund Wedam Kanmiki
- UQ Poche Centre for Indigenous Health, The University of Queensland, Brisbane, 74 High Street Toowong, Queensland, 4066, Australia
| | - Stuart Leske
- UQ Poche Centre for Indigenous Health, The University of Queensland, Brisbane, 74 High Street Toowong, Queensland, 4066, Australia
| | - Janet Stajic
- UQ Poche Centre for Indigenous Health, The University of Queensland, Brisbane, 74 High Street Toowong, Queensland, 4066, Australia
| | - James Ward
- UQ Poche Centre for Indigenous Health, The University of Queensland, Brisbane, 74 High Street Toowong, Queensland, 4066, Australia
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Akazili J, Kanmiki EW, Anaseba D, Govender V, Danhoundo G, Koduah A. Challenges and facilitators to the provision of sexual, reproductive health and rights services in Ghana. Sex Reprod Health Matters 2020; 28:1846247. [PMID: 33213298 PMCID: PMC7888097 DOI: 10.1080/26410397.2020.1846247] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
Expanding access to sexual and reproductive health (SRH) services is one of the key targets of the Sustainable Development Goals. The extent to which sexual and reproductive health and rights (SRHR) targets will be achieved largely depends on how well they are integrated within Universal Health Coverage (UHC) initiatives. This paper examines challenges and facilitators to the effective provision of three SRHR services (maternal health, gender-based violence (GBV) and safe abortion/post-abortion care) in Ghana. The analysis triangulates evidence from document review with in-depth qualitative stakeholder interviews and adopts the Donabedian framework in evaluating provision of these services. Critical among the challenges identified are inadequate funding, non-inclusion of some SRHR services including family planning and abortion/post-abortion services within the health benefits package and hidden charges for maternal services. Other issues are poor supervision, maldistribution of logistics and health personnel, fragmentation of support services for GBV victims across agencies, and socio-cultural and religious beliefs and practices affecting service delivery and utilisation. Facilitators that hold promise for effective SRH service delivery include stakeholder collaboration and support, health system structure that supports continuum of care, availability of data for monitoring progress and setting priorities, and an effective process for sharing lessons and accountability through frequent review meetings. We propose the development of a national master plan for SRHR integration within UHC initiatives in the country. Addressing the financial, logistical and health worker shortages and maldistribution will go a long way to propel Ghana's efforts to expand population coverage, service coverage and financial risk protection in accessing essential SRH services.
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Affiliation(s)
- James Akazili
- Deputy Director, Research and Development Division, Ghana Health Service Headquarters, Accra, Ghana. Correspondence:
| | - Edmund Wedam Kanmiki
- PhD Candidate, Institute for Social Science Research, The University of Queensland, Indooroopilly, QLD, Australia
| | - Dominic Anaseba
- Health Planning Officer, Policy, Planning, Monitoring and Evaluation Division, Ghana Health Service Headquarters, Accra, Ghana
| | - Veloshnee Govender
- Scientist, Department of Reproductive Health and Research, World Health Organization, Geneva, Switzerland
| | - Georges Danhoundo
- Scientist, Department of Reproductive Health and Research, World Health Organization, Geneva, Switzerland
| | - Augustina Koduah
- Lecturer, Department of Pharmacy Practice and Clinical Pharmacy, School of Pharmacy, University of Ghana, Accra, Ghana
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Kanmiki EW, Bawah AA, Akazili J, Agorinyah I, Awoonor-Williams JK, Phillips JF, Kassak KM. Unawareness of health insurance expiration status among women of reproductive age in Northern Ghana: implications for achieving universal health coverage. J Health Popul Nutr 2019; 38:34. [PMID: 31775904 PMCID: PMC6882328 DOI: 10.1186/s41043-019-0190-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/22/2018] [Accepted: 10/01/2019] [Indexed: 06/10/2023]
Abstract
BACKGROUND Ghana implemented a national health insurance scheme in 2005 to promote the provision of accessible, affordable, and equitable healthcare by eliminating service user fees. Termed the National Health Insurance Scheme (NHIS), its active enrollment has remained low despite a decade of program implementation. This study assesses factors explaining this problem by examining the correlates of insurance status unawareness among women of reproductive age. METHODS In 2015, a random probability cross-sectional survey of 5914 reproductive-aged women was compiled in the Upper East Region, an impoverished and remote region in Northern Ghana. During the survey, two questions related to the NHIS were asked: "Have you ever registered with the NHIS?" and "Do you currently have a valid NHIS card?" If the answer to the second question was yes, the respondents were requested to show their insurance card, thereby enabling interviewers to determine if the NHIS requirement of annual renewal had been met. Results are based on the tabulation of the prevalence of unawareness status, tests of bivariate associations, and multivariate estimation of regression adjusted effects. RESULTS Of the 5914 respondents, 3614 (61.1%) who reported that they were actively enrolled in the NHIS could produce their insurance cards upon request. Of these respondents, 1243 (34.4%) had expired cards. Factors that significantly predicted unawareness of card expiration were occupation, district of residence, and socio-economic status. Relative to other occupational categories, farmers were the most likely to be unaware of their card invalidity. Respondents residing in three of the study districts were less aware of their insurance card validity than the other four study districts. Unawareness was observed to increase monotonically with relative poverty. CONCLUSION Unawareness of insurance care validity status contributes to low active enrollment in Ghana's NHIS. Educational messages aimed at improving health insurance coverage should include the promotion of annual renewal and also should focus on the information needs of farmers and low socio-economic groups.
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Affiliation(s)
| | - Ayaga A. Bawah
- Regional Institute for Population Studies, University of Ghana, Accra, Ghana
| | - James Akazili
- Research and Development Division, Ghana Health Service, Accra, Ghana
| | - Isaiah Agorinyah
- Swiss Tropical and Public Health Institute, University of Basel, Basel, Switzerland
| | | | - James F. Phillips
- Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York City, USA
| | - Kassem M. Kassak
- Department of Health Management and Policy, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
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Kanmiki EW, Bawah AA, Phillips JF, Awoonor-Williams JK, Kachur SP, Asuming PO, Agula C, Akazili J. Out-of-pocket payment for primary healthcare in the era of national health insurance: Evidence from northern Ghana. PLoS One 2019; 14:e0221146. [PMID: 31430302 PMCID: PMC6701750 DOI: 10.1371/journal.pone.0221146] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Accepted: 07/31/2019] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Ghana introduced a national health insurance program in 2005 with the goal of removing user fees, popularly called "cash and carry", along with their associated catastrophic and impoverishment effects on the population and ensuring access to equitable health care. However, after a decade of implementation, the impact of this program on user fees and out-of-pocket payment (OOP) is not properly documented. This paper contributes to understanding the impact of Ghana's health insurance program on out-of-pocket healthcare payments and the factors associated with the level of out-of-pocket payments for primary healthcare in a predominantly rural region of Ghana. METHODS Using a five-year panel data of revenues accruing to public primary health facilities in seven districts, We employed mean comparison tests (t-test) to examine the trend in revenues accruing from out-of-pocket payments vis-à-vis health insurance claims for health services, medication, and obstetric care. Furthermore, generalized estimation equation regression models were used to assess the relationship between explanatory variables and the level of out-of-pocket payments and health insurance claims. RESULTS Out-of-pocket payment for health services and medications declined by 63% and 62% respectively between 2010 and 2014. Insurance claims however increased by 16% within the same period. There was statistically a significant mean reduction in out-of-pocket payment over the period. Factors significantly associated with out-of-pocket payments in a given district are the number of community health facilities, availability of a district hospital and the year of observation. CONCLUSION The study provides evidence that Ghana's national health insurance program is significantly contributing to a reduction in out-of-pocket payment for primary healthcare in public health facilities. Efforts should therefore be put in place to ensure the sustainability of this policy as a major pathway for achieving universal health coverage in Ghana.
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Affiliation(s)
- Edmund Wedam Kanmiki
- Regional Institute for Population Studies, University of Ghana, Accra, Ghana
- * E-mail:
| | - Ayaga A. Bawah
- Regional Institute for Population Studies, University of Ghana, Accra, Ghana
| | - James F. Phillips
- Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York, New York, United States of America
| | | | - S. Patrick Kachur
- Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York, New York, United States of America
| | | | - Caesar Agula
- Regional Institute for Population Studies, University of Ghana, Accra, Ghana
| | - James Akazili
- Navrongo Health Research Centre, Ghana Health Service, Navrongo, Upper East Region, Ghana
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Kanmiki EW, Bempah BOS, Awoonor-Williams JK, Bawah AA, d’Almeida SA, Kassak KM. An assessment of a performance-based management agreement initiative in Ghana's health service. BMC Health Serv Res 2018; 18:995. [PMID: 30587171 PMCID: PMC6307131 DOI: 10.1186/s12913-018-3810-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2017] [Accepted: 12/11/2018] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND As part of its efforts to improve efficiency, accountability and overall performance, the Ghana Health Service (GHS) introduced annual Performance-based Management Agreements (PMAs) in the year 2013. However, no assessment of this initiative has since been made in order to inform policy and practice. This paper provides an assessment of this policy initiative from the perspective of managers at various levels of service implementation. METHODS Mixed methods were employed. Questionnaires were administered to managers through an online survey (using Google forms). Descriptive and inferential statistical methods were used to analyze and present quantitative results while qualitative data was analyzed via thematic analysis. RESULTS The content and objectives of the PMAs were observed to be comprehensive and directed at ensuring high performance of directorates. Targets of PMAs were found to be aligned with overall health sector objectives and priorities. The directors felt PMAs were useful for delegating task to subordinates. PMAs were also found to increase commitment and contributed to improving teamwork and prudent use of resources. However, PMAs were found to lack clear implementation strategies and were not backed by incentives and sanctions. Also, budgetary allocations did not reflect demands of PMAs. Furthermore, directors at lower levels were not adequately consulted in setting PMAs targets as such district specific challenges and priorities are not usually factored into the process. Insufficient training of staff and lack of requisite staff were key challenges confronting the implementation of PMAs in most directorates. Weak monitoring and evaluation was also observed to significantly affect the success of PMAs. CONCLUSION There is the need to address the weaknesses and improve on the existing strengths identified by this assessment in order to enhance the effectiveness of PMAs utilization in the Ghana health service.
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Affiliation(s)
| | - Ben Owusu Smith Bempah
- Policy, Planning, Monitoring and Evaluation Division, Ghana Health Service, Accra, Ghana
| | | | - Ayaga A. Bawah
- Regional Institute for Population Studies, University of Ghana, Accra, Ghana
| | | | - Kassem M. Kassak
- Department of Health Management and Policy, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
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Akazili J, Chatio S, Ataguba JEO, Agorinya I, Kanmiki EW, Sankoh O, Oduro A. Informal workers' access to health care services: findings from a qualitative study in the Kassena-Nankana districts of Northern Ghana. BMC Int Health Hum Rights 2018; 18:20. [PMID: 29769071 PMCID: PMC5956930 DOI: 10.1186/s12914-018-0159-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 04/10/2017] [Accepted: 05/07/2018] [Indexed: 11/22/2022]
Abstract
Background Over the past two decades, employment in the informal sector has grown rapidly in all regions including low and middle-income countries. In the developing countries, between 50 and 75% of workers are employed in the informal sector. In Ghana, more than 80% of the total working population is working in the informal sector. They are largely self-employed persons such as farmers, traders, food processors, artisans, craft-workers among others. The persistent problem in advancing efforts to address health vulnerabilities of informal workers is lack of systematic data. Therefore, this study explored factors affecting informal workers access to health care services in Northern Ghana. Method The study used qualitative methodology where focus group discussions and in-depth interviews were conducted. Purposive sampling technique was used to select participants for the interviews. The interviews were transcribed and coded into emergent themes using Nvivo 10 software before thematic content analysis. Results Study participants held the view that factors such as poverty, time spent at the health facility seeking for health care, unpleasant attitude of health providers towards clients affected their access to health care services. They perceived that poor organization and operations of the current health system and poor health care services provided under the national health insurance scheme affected access to health care services according to study participants. However, sale of assets, family support, borrowed money from friends and occasional employer support were the copying strategies used by informal workers to finance their health care needs. Conclusion Most of the population in Ghana are engaged in informal employment hence their contribution to the economy is very important. Therefore, efforts needed to be made by all stakeholders to address these challenges in order to help improve on access to health care services to all patients particularly the most vulnerable groups in society.
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Affiliation(s)
- James Akazili
- Navrongo Health Research Centre, P.O Box 114, Navrongo, Ghana. .,INDEPTH Network, P.O Box KD 213, Kanda, Accra, Ghana.
| | - Samuel Chatio
- Navrongo Health Research Centre, P.O Box 114, Navrongo, Ghana
| | | | - Isaiah Agorinya
- Navrongo Health Research Centre, P.O Box 114, Navrongo, Ghana
| | | | - Osman Sankoh
- INDEPTH Network, P.O Box KD 213, Kanda, Accra, Ghana.,School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.,Department of Mathematics and Statistics, Njala University, Njala, Sierra Leone
| | - Abraham Oduro
- Navrongo Health Research Centre, P.O Box 114, Navrongo, Ghana
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Akazili J, Ataguba JEO, Kanmiki EW, Gyapong J, Sankoh O, Oduro A, McIntyre D. Assessing the impoverishment effects of out-of-pocket healthcare payments prior to the uptake of the national health insurance scheme in Ghana. BMC Int Health Hum Rights 2017; 17:13. [PMID: 28532403 PMCID: PMC5440955 DOI: 10.1186/s12914-017-0121-7] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/30/2016] [Accepted: 05/14/2017] [Indexed: 11/10/2022]
Abstract
BACKGROUND There is a global concern regarding how households could be protected from relatively large healthcare payments which are a major limitation to accessing healthcare. Such payments also endanger the welfare of households with the potential of moving households into extreme impoverishment. This paper examines the impoverishing effects of out-of-pocket (OOP) healthcare payments in Ghana prior to the introduction of Ghana's national health insurance scheme. METHODS Data come from the Ghana Living Standard Survey 5 (2005/2006). Two poverty lines ($1.25 and $2.50 per capita per day at the 2005 purchasing power parity) are used in assessing the impoverishing effects of OOP healthcare payments. We computed the poverty headcount, poverty gap, normalized poverty gap and normalized mean poverty gap indices using both poverty lines. We examine these indicators at a national level and disaggregated by urban/rural locations, across the three geographical zones, and across the ten administrative regions in Ghana. Also the Pen's parade of "dwarfs and a few giants" is used to illustrate the decreasing welfare effects of OOP healthcare payments in Ghana. RESULTS There was a high incidence and intensity of impoverishment due to OOP healthcare payments in Ghana. These payments contributed to a relative increase in poverty headcount by 9.4 and 3.8% using the $1.25/day and $2.5/day poverty lines, respectively. The relative poverty gap index was estimated at 42.7 and 10.5% respectively for the lower and upper poverty lines. Relative normalized mean poverty gap was estimated at 30.5 and 6.4%, respectively, for the lower and upper poverty lines. The percentage increase in poverty associated with OOP healthcare payments in Ghana is highest among households in the middle zone with an absolute increase estimated at 2.3% compared to the coastal and northern zones. CONCLUSION It is clear from the findings that without financial risk protection, households can be pushed into poverty due to OOP healthcare payments. Even relatively richer households are impoverished by OOP healthcare payments. This paper presents baseline indicators for evaluating the impact of Ghana's national health insurance scheme on impoverishment due to OOP healthcare payments.
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Affiliation(s)
- James Akazili
- Navrongo Health Research Centre, Ghana Health Service, Box 114, Navrongo, Upper East Region Ghana
- INDEPTH Network, Kanda, P.O. Box KD 213, Accra, Ghana
| | - John Ele-Ojo Ataguba
- Health Economics Unit, School of Public Health and Family Medicine, Faculty of Health Sciences, University of Cape Town, Observatory, South Africa
| | - Edmund Wedam Kanmiki
- Navrongo Health Research Centre, Ghana Health Service, Box 114, Navrongo, Upper East Region Ghana
| | - John Gyapong
- University of Health and Allied Sciences, PMB 31 Ho, Ghana
| | - Osman Sankoh
- School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Abraham Oduro
- Navrongo Health Research Centre, Ghana Health Service, Box 114, Navrongo, Upper East Region Ghana
| | - Di McIntyre
- Health Economics Unit, School of Public Health and Family Medicine, Faculty of Health Sciences, University of Cape Town, Observatory, South Africa
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Kanmiki EW, Bawah AA, Agorinya I, Achana FS, Awoonor-williams JK, Oduro AR, Phillips JF, Akazili J. Socio-economic and demographic determinants of under-five mortality in rural northern Ghana. BMC Int Health Hum Rights 2014; 14:24. [PMID: 25145383 PMCID: PMC4144693 DOI: 10.1186/1472-698x-14-24] [Citation(s) in RCA: 65] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 05/20/2014] [Accepted: 08/13/2014] [Indexed: 12/01/2022]
Abstract
BACKGROUND In spite of global decline in under-five mortality, the goal of achieving MDG 4 still remains largely unattained in low and middle income countries as the year 2015 closes-in. To accelerate the pace of mortality decline, proven interventions with high impact need to be implemented to help achieve the goal of drastically reducing childhood mortality. This paper explores the association between socio-economic and demographic factors and under-five mortality in an impoverished region in rural northern Ghana. METHODS We used survey data on 3975 women aged 15-49 who have ever given birth. First, chi-square test was used to test the association of social, economic and demographic characteristics of mothers with the experience of under-five death. Subsequently, we ran a logistic regression model to estimate the relative association of factors that influence childhood mortality after excluding variables that were not significant at the bivariate level. RESULTS Factors that significantly predict under-five mortality included mothers' educational level, presence of co-wives, age and marital status. Mothers who have achieved primary or junior high school education were 45% less likely to experience under-five death than mothers with no formal education at all (OR = 0.55, p < 0.001). Monogamous women were 22% less likely to experience under-five deaths than mothers in polygamous marriages (OR = 0.78, p = 0.01). Similarly, mothers who were between the ages of 35 and 49 were about eleven times more likely to experience under-five deaths than those below the age of 20 years (OR = 11.44, p < 0.001). Also, women who were married had a 27% less likelihood (OR = 0.73, p = 0.01) of experiencing an under-five death than those who were single, divorced or widowed. CONCLUSION Taken independently, maternal education, age, marital status and presence of co-wives are associated with childhood mortality. The relationship of these indicators with women's autonomy, health seeking behavior, and other factors that affect child survival merit further investigation so that interventions could be designed to foster reductions in child mortality by considering the needs and welfare of women including the need for female education, autonomy and socioeconomic well-being.
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Affiliation(s)
- Edmund Wedam Kanmiki
- Navrongo Health Research Centre, Ghana Health Service, Upper East Region, Box 114, Navrongo, Ghana
| | - Ayaga A Bawah
- Department of Population and Family Health, Mailman School of Public Health, Columbia University, Columbia, USA
| | - Isaiah Agorinya
- Navrongo Health Research Centre, Ghana Health Service, Upper East Region, Box 114, Navrongo, Ghana
| | - Fabian S Achana
- Navrongo Health Research Centre, Ghana Health Service, Upper East Region, Box 114, Navrongo, Ghana
| | | | - Abraham R Oduro
- Navrongo Health Research Centre, Ghana Health Service, Upper East Region, Box 114, Navrongo, Ghana
| | - James F Phillips
- Department of Population and Family Health, Mailman School of Public Health, Columbia University, Columbia, USA
| | - James Akazili
- Navrongo Health Research Centre, Ghana Health Service, Upper East Region, Box 114, Navrongo, Ghana
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