35 research outputs found

    Falls Predict Acute Hospitalization in Parkinson's Disease

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    Malaltia de Parkinson; Levodopa; Factors de riscEnfermedad de Parkinson; Levodopa; Factores de riesgoParkinson Disease; Levodopa; Risk FactorsBackground:There is a need for identifying risk factors for hospitalization in Parkinson’s disease (PD) and also interventions to reduce acute hospital admission. Objective:To analyze the frequency, causes, and predictors of acute hospitalization (AH) in PD patients from a Spanish cohort.Methods:PD patients recruited from 35 centers of Spain from the COPPADIS-2015 (COhort of Patients with PArkinson’s DIsease in Spain, 2015) cohort from January 2016 to November 2017, were included in the study. In order to identify predictors of AH, Kaplan-Meier estimates of factors considered as potential predictors were obtained and Cox regression performed on time to hospital encounter 1-year after the baseline visit.Results:Thirty-five out of 605 (5.8%) PD patients (62.5±8.9 years old; 59.8% males) presented an AH during the 1-year follow-up after the baseline visit. Traumatic falls represented the most frequent cause of admission, being 23.7% of all acute hospitalizations. To suffer from motor fluctuations (HR [hazard ratio] 2.461; 95% CI, 1.065–5.678; p = 0.035), a very severe non-motor symptoms burden (HR [hazard ratio] 2.828; 95% CI, 1.319–6.063; p = 0.008), falls (HR 3.966; 95% CI 1.757–8.470; p = 0.001), and dysphagia (HR 2.356; 95% CI 1.124–4.941; p = 0.023) was associated with AH after adjustment to age, gender, disease duration, levodopa equivalent daily dose, total number of non-antiparkinsonian drugs, and UPDRS-IIIOFF. Of the previous variables, only falls (HR 2.998; 95% CI 1.080–8.322; p = 0.035) was an independent predictor of AH. Conclusion:Falls is an independent predictor of AH in PD patient

    Motor Fluctuations Development Is Associated with Non-Motor Symptoms Burden Progression in Parkinson’s Disease Patients: A 2-Year Follow-Up Study

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    Parkinson’s disease; Motor fluctuations; Non-motor symptomsEnfermedad de Parkinson; Fluctuaciones motoras; SĂ­ntomas no motoresMalaltia de Parkinson; Fluctuacions motrius; SĂ­mptomes no motorsThe aim of the present study was to analyze the progression of non-motor symptoms (NMS) burden in Parkinson’s disease (PD) patients regarding the development of motor fluctuations (MF). Methods: PD patients without MF at baseline, who were recruited from January 2016 to November 2017 (V0) and evaluated again at a 2-year follow-up (V2) from 35 centers of Spain from the COPPADIS cohort, were included in this analysis. MF development at V2 was defined as a score ≄ 1 in the item-39 of the UPDRS-Part IV, whereas NMS burden was defined according to the Non-motor Symptoms Scale (NMSS) total score. Results: Three hundred and thirty PD patients (62.67 ± 8.7 years old; 58.8% males) were included. From V0 to V2, 27.6% of the patients developed MF. The mean NMSS total score at baseline was higher in those patients who developed MF after the 2-year follow-up (46.34 ± 36.48 vs. 34.3 ± 29.07; p = 0.001). A greater increase in the NMSS total score from V0 to V2 was observed in patients who developed MF (+16.07 ± 37.37) compared to those who did not develop MF (+6.2 ± 25.8) (p = 0.021). Development of MF after a 2-year follow-up was associated with an increase in the NMSS total score (ÎČ = 0.128; p = 0.046) after adjustment to age, gender, years from symptoms onset, levodopa equivalent daily dose (LEDD) and the NMSS total score at baseline, and the change in LEDD from V0 to V2. Conclusions: In PD patients, the development of MF is associated with a greater increase in the NMS burden after a 2-year follow-up

    Psychological and occlusal therapies in patient with bruxism

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    Se realiza un estudio de intervención para evaluar la efectividad de las terapias psicológicas y oclusales en pacientes bruxómanos. El universo de estudio estå constituido por 50 pacientes con diagnóstico clínico de bruxismo. Se establecieron dos grupos de estudio: grupo 1 se le implementó terapia psicológica con el obturador nasal transicional y al grupo 2 la terapia oclusal con el uso de férula oclusal. El estudio realizado revela cambios que modifican el estado de salud de pacientes bruxómanos, con la introducción de la terapia de modificación de conducta con el uso del obturador nasal transicional. An intervention study is done for assessing the effectiveness of psychological therapies and occlusal in patients with bruxism. The universe was constituted by 50 patients with clinical diagnosis of bruxism. Two study-groups were established: In Group 1 was implemented psychological therapy with transitional nasal shutter and the Group 2 occlusal therapy using occlusal splint. The study already done reveals several changes that modify the state of health on patients with bruxism, with the introduction of behavior modification therapy with the use of nasal transitional shutter

    Falls predict acute hospitalization in Parkinson's disease

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    Background: There is a need for identifying risk factors for hospitalization in Parkinson's disease (PD) and also interventions to reduce acute hospital admission. Objective: To analyze the frequency, causes, and predictors of acute hospitalization (AH) in PD patients from a Spanish cohort. Methods: PD patients recruited from 35 centers of Spain from the COPPADIS-2015 (COhort of Patients with PArkinson's DIsease in Spain, 2015) cohort from January 2016 to November 2017, were included in the study. In order to identify predictors of AH, Kaplan-Meier estimates of factors considered as potential predictors were obtained and Cox regression performed on time to hospital encounter 1-year after the baseline visit. Results: Thirty-five out of 605 (5.8%) PD patients (62.5±8.9 years old; 59.8% males) presented an AH during the 1-year follow-up after the baseline visit. Traumatic falls represented the most frequent cause of admission, being 23.7% of all acute hospitalizations. To suffer from motor fluctuations (HR [hazard ratio] 2.461; 95% CI, 1.065-5.678; p = 0.035), a very severe non-motor symptoms burden (HR [hazard ratio] 2.828; 95% CI, 1.319-6.063; p = 0.008), falls (HR 3.966; 95% CI 1.757-8.470; p = 0.001), and dysphagia (HR 2.356; 95% CI 1.124-4.941; p = 0.023) was associated with AH after adjustment to age, gender, disease duration, levodopa equivalent daily dose, total number of non-antiparkinsonian drugs, and UPDRS-IIIOFF. Of the previous variables, only falls (HR 2.998; 95% CI 1.080-8.322; p = 0.035) was an independent predictor of AH. Conclusion: Falls is an independent predictor of AH in PD patients

    Staging Parkinson's Disease Combining Motor and Nonmotor Symptoms Correlates with Disability and Quality of Life.

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    Introduction: In a degenerative disorder such as Parkinson's disease (PD), it is important to establish clinical stages that allow to know the course of the disease. Our aim was to analyze whether a scale combining Hoehn and Yahr's motor stage (H&Y) and the nonmotor symptoms burden (NMSB) (assessed by the nonmotor symptoms scale (NMSS)) provides information about the disability and the patient's quality of life (QoL) with regard to a defined clinical stage. Materials and methods: Cross-sectional study in which 603 PD patients from the COPPADIS cohort were classified according to H&Y (1, stage I; 2, stage II; 3, stage III; 4, stage IV/V) and NMSB (A: NMSS = 0-20; B: NMSS = 21-40; C: NMSS = 41-70; D: NMSS ≄ 71) in 16 stages (HY.NMSB, from 1A to 4D). QoL was assessed with the PDQ-39SI, PQ-10, and EUROHIS-QOL8 and disability with the Schwab&England ADL (Activities of Daily Living) scale. Results: A worse QoL and greater disability were observed at a higher stage of H&Y and NMSB (p < 0.0001). Combining both (HY.NMSB), patients in stages 1C and 1D and 2C and 2D had significantly worse QoL and/or less autonomy for ADL than those in stages 2A and 2B and 3A and 3B, respectively (p < 0.005; e.g., PDQ-39SI in 1D [n = 15] vs 2A [n = 101]: 28.6 ± 17.1 vs 7.9 ± 5.8; p < 0.0001). Conclusion: The HY.NMSB scale is simple and reflects the degree of patient involvement more accurately than the HΚ Patients with a lower H&Y stage may be more affected if they have a greater NMS burden

    Treatment with tocilizumab or corticosteroids for COVID-19 patients with hyperinflammatory state: a multicentre cohort study (SAM-COVID-19)

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    Objectives: The objective of this study was to estimate the association between tocilizumab or corticosteroids and the risk of intubation or death in patients with coronavirus disease 19 (COVID-19) with a hyperinflammatory state according to clinical and laboratory parameters. Methods: A cohort study was performed in 60 Spanish hospitals including 778 patients with COVID-19 and clinical and laboratory data indicative of a hyperinflammatory state. Treatment was mainly with tocilizumab, an intermediate-high dose of corticosteroids (IHDC), a pulse dose of corticosteroids (PDC), combination therapy, or no treatment. Primary outcome was intubation or death; follow-up was 21 days. Propensity score-adjusted estimations using Cox regression (logistic regression if needed) were calculated. Propensity scores were used as confounders, matching variables and for the inverse probability of treatment weights (IPTWs). Results: In all, 88, 117, 78 and 151 patients treated with tocilizumab, IHDC, PDC, and combination therapy, respectively, were compared with 344 untreated patients. The primary endpoint occurred in 10 (11.4%), 27 (23.1%), 12 (15.4%), 40 (25.6%) and 69 (21.1%), respectively. The IPTW-based hazard ratios (odds ratio for combination therapy) for the primary endpoint were 0.32 (95%CI 0.22-0.47; p < 0.001) for tocilizumab, 0.82 (0.71-1.30; p 0.82) for IHDC, 0.61 (0.43-0.86; p 0.006) for PDC, and 1.17 (0.86-1.58; p 0.30) for combination therapy. Other applications of the propensity score provided similar results, but were not significant for PDC. Tocilizumab was also associated with lower hazard of death alone in IPTW analysis (0.07; 0.02-0.17; p < 0.001). Conclusions: Tocilizumab might be useful in COVID-19 patients with a hyperinflammatory state and should be prioritized for randomized trials in this situatio

    Falls Predict Acute Hospitalization in Parkinson's Disease

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    [Background] There is a need for identifying risk factors for hospitalization in Parkinson’s disease (PD) and also interventions to reduce acute hospital admission.[Objective] To analyze the frequency, causes, and predictors of acute hospitalization (AH) in PD patients from a Spanish cohort.[Methods] PD patients recruited from 35 centers of Spain from the COPPADIS-2015 (COhort of Patients with PArkinson’s DIsease in Spain, 2015) cohort from January 2016 to November 2017, were included in the study. In order to identify predictors of AH, Kaplan-Meier estimates of factors considered as potential predictors were obtained and Cox regression performed on time to hospital encounter 1-year after the baseline visit.[Results] Thirty-five out of 605 (5.8%) PD patients (62.5±8.9 years old; 59.8% males) presented an AH during the 1-year follow-up after the baseline visit. Traumatic falls represented the most frequent cause of admission, being 23.7% of all acute hospitalizations. To suffer from motor fluctuations (HR [hazard ratio] 2.461; 95% CI, 1.065–5.678; p = 0.035), a very severe non-motor symptoms burden (HR [hazard ratio] 2.828; 95% CI, 1.319–6.063; p = 0.008), falls (HR 3.966; 95% CI 1.757–8.470; p = 0.001), and dysphagia (HR 2.356; 95% CI 1.124–4.941; p = 0.023) was associated with AH after adjustment to age, gender, disease duration, levodopa equivalent daily dose, total number of non-antiparkinsonian drugs, and UPDRS-IIIOFF. Of the previous variables, only falls (HR 2.998; 95% CI 1.080–8.322; p = 0.035) was an independent predictor of AH.[Conclusion] Falls is an independent predictor of AH in PD patients.Peer reviewe

    Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019 : A systematic analysis for the Global Burden of Disease Study 2019

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    Background Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≄65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010–2019 relative to 1990–2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach 1398pooledhealthspendingpercapita(US1398 pooled health spending per capita (US adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6–421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0–3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5–1040·3]) residing in south Asia. Interpretation The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people—the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close—or how far—all populations are in benefiting from UHC

    Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

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    Background Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≄65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010–2019 relative to 1990–2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach 1398pooledhealthspendingpercapita(US1398 pooled health spending per capita (US adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6–421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0–3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5–1040·3]) residing in south Asia. Interpretation The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people—the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close—or how far—all populations are in benefiting from UHC

    Population and fertility by age and sex for 195 countries and territories, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017

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    Background: Population estimates underpin demographic and epidemiological research and are used to track progress on numerous international indicators of health and development. To date, internationally available estimates of population and fertility, although useful, have not been produced with transparent and replicable methods and do not use standardised estimates of mortality. We present single-calendar year and single-year of age estimates of fertility and population by sex with standardised and replicable methods. Methods: We estimated population in 195 locations by single year of age and single calendar year from 1950 to 2017 with standardised and replicable methods. We based the estimates on the demographic balancing equation, with inputs of fertility, mortality, population, and migration data. Fertility data came from 7817 location-years of vital registration data, 429 surveys reporting complete birth histories, and 977 surveys and censuses reporting summary birth histories. We estimated age-specific fertility rates (ASFRs; the annual number of livebirths to women of a specified age group per 1000 women in that age group) by use of spatiotemporal Gaussian process regression and used the ASFRs to estimate total fertility rates (TFRs; the average number of children a woman would bear if she survived through the end of the reproductive age span [age 10–54 years] and experienced at each age a particular set of ASFRs observed in the year of interest). Because of sparse data, fertility at ages 10–14 years and 50–54 years was estimated from data on fertility in women aged 15–19 years and 45–49 years, through use of linear regression. Age-specific mortality data came from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 estimates. Data on population came from 1257 censuses and 761 population registry location-years and were adjusted for underenumeration and age misreporting with standard demographic methods. Migration was estimated with the GBD Bayesian demographic balancing model, after incorporating information about refugee migration into the model prior. Final population estimates used the cohort-component method of population projection, with inputs of fertility, mortality, and migration data. Population uncertainty was estimated by use of out-of-sample predictive validity testing. With these data, we estimated the trends in population by age and sex and in fertility by age between 1950 and 2017 in 195 countries and territories. Findings: From 1950 to 2017, TFRs decreased by 49·4% (95% uncertainty interval [UI] 46·4–52·0). The TFR decreased from 4·7 livebirths (4·5–4·9) to 2·4 livebirths (2·2–2·5), and the ASFR of mothers aged 10–19 years decreased from 37 livebirths (34–40) to 22 livebirths (19–24) per 1000 women. Despite reductions in the TFR, the global population has been increasing by an average of 83·8 million people per year since 1985. The global population increased by 197·2% (193·3–200·8) since 1950, from 2·6 billion (2·5–2·6) to 7·6 billion (7·4–7·9) people in 2017; much of this increase was in the proportion of the global population in south Asia and sub-Saharan Africa. The global annual rate of population growth increased between 1950 and 1964, when it peaked at 2·0%; this rate then remained nearly constant until 1970 and then decreased to 1·1% in 2017. Population growth rates in the southeast Asia, east Asia, and Oceania GBD super-region decreased from 2·5% in 1963 to 0·7% in 2017, whereas in sub-Saharan Africa, population growth rates were almost at the highest reported levels ever in 2017, when they were at 2·7%. The global average age increased from 26·6 years in 1950 to 32·1 years in 2017, and the proportion of the population that is of working age (age 15–64 years) increased from 59·9% to 65·3%. At the national level, the TFR decreased in all countries and territories between 1950 and 2017; in 2017, TFRs ranged from a low of 1·0 livebirths (95% UI 0·9–1·2) in Cyprus to a high of 7·1 livebirths (6·8–7·4) in Niger. The TFR under age 25 years (TFU25; number of livebirths expected by age 25 years for a hypothetical woman who survived the age group and was exposed to current ASFRs) in 2017 ranged from 0·08 livebirths (0·07–0·09) in South Korea to 2·4 livebirths (2·2–2·6) in Niger, and the TFR over age 30 years (TFO30; number of livebirths expected for a hypothetical woman ageing from 30 to 54 years who survived the age group and was exposed to current ASFRs) ranged from a low of 0·3 livebirths (0·3–0·4) in Puerto Rico to a high of 3·1 livebirths (3·0–3·2) in Niger. TFO30 was higher than TFU25 in 145 countries and territories in 2017. 33 countries had a negative population growth rate from 2010 to 2017, most of which were located in central, eastern, and western Europe, whereas population growth rates of more than 2·0% were seen in 33 of 46 countries in sub-Saharan Africa. In 2017, less than 65% of the national population was of working age in 12 of 34 high-income countries, and less than 50% of the national population was of working age in Mali, Chad, and Niger. Interpretation: Population trends create demographic dividends and headwinds (ie, economic benefits and detriments) that affect national economies and determine national planning needs. Although TFRs are decreasing, the global population continues to grow as mortality declines, with diverse patterns at the national level and across age groups. To our knowledge, this is the first study to provide transparent and replicable estimates of population and fertility, which can be used to inform decision making and to monitor progress
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