83 research outputs found
Nexus between PI3K/AKT and Estrogen Receptor Signaling in Breast Cancer
Signaling from estrogen receptor alpha (ERα) and its ligand estradiol (E2) is critical for growth of ≈70% of breast cancers. Therefore, several drugs that inhibit ERα functions have been in clinical use for decades and new classes of anti-estrogens are continuously being developed. Although a significant number of ERα+ breast cancers respond to anti-estrogen therapy, ≈30% of these breast cancers recur, sometimes even after 20 years of initial diagnosis. Mechanism of resistance to anti-estrogens is one of the intensely studied disciplines in breast cancer. Several mechanisms have been proposed including mutations in ESR1, crosstalk between growth factor and ERα signaling, and interplay between cell cycle machinery and ERα signaling. ESR1 mutations as well as crosstalk with other signaling networks lead to ligand independent activation of ERα thus rendering anti-estrogens ineffective, particularly when treatment involved anti-estrogens that do not degrade ERα. As a result of these studies, several therapies that combine anti-estrogens that degrade ERα with PI3K/AKT/mTOR inhibitors targeting growth factor signaling or CDK4/6 inhibitors targeting cell cycle machinery are used clinically to treat recurrent ERα+ breast cancers. In this review, we discuss the nexus between ERα-PI3K/AKT/mTOR pathways and how understanding of this nexus has helped to develop combination therapies
Blood pressure control and left ventricular hypertrophy in hypertensive Nigerians
Background : Hypertension is a disease characterized by end-organ
complications, leading to high morbidity and mortality in many cases.
People with untreated or uncontrolled hypertension often run the risk
of developing complications directly associated with the disease. Left
ventricular hypertrophy (LVH) has been shown to be a significant risk
factor for adverse outcomes both in patients with hypertension and in
the general population. We investigated the prevalence and pattern of
LVH in a treated hypertensive population at the University College
Hospital, Ibadan, Nigeria, using non-hypertensive subjects as control.
Design and Setting : A prospective observational study performed at the
University College Hospital, Ibadan, Nigeria. Methods : Patients had 6
visits, when at least one blood pressure measurement was recorded for
each hypertensive subject and average calculated for systolic blood
pressure (SBP) and diastolic blood pressure (DBP) separately. The
values obtained were used for stratification of the subjects into
controlled and uncontrolled hypertension. Subjects also had
echocardiograms to determine their left ventricular mass. Results :
LVH was found in 14 (18.2%) of the normotensive group, 40 (20.8%) of
the uncontrolled hypertensive group and 14 (24.1%) of the controlled
hypertensive group when left ventricular mass (LVM) was indexed to body
surface area (BSA). When LVM was indexed to height, left ventricular
hypertrophy was found in none of the subjects of the normotensive
group, while it was found present in 43 (22.4%) and 14 (24.1%) subjects
of the uncontrolled and controlled hypertensive groups, respectively.
Significant difference in the prevalence of LVH was detected only when
LVM was indexed to height alone. Conclusion : Clinic blood pressure is
an ineffective way of assessing BP control. Thus in apparently
controlled hypertensive subjects, based on office blood pressure,
cardiac structural changes do remain despite antihypertensive therapy.
This population is still at risk of cardiovascular events.arri\ue8re-plan: l\u2019hypertension est une maladie
caract\ue9ris\ue9e par l\u2019orgue de fi n complications menant
\ue0 \ue9lev\ue9 de morbidit\ue9 et mortalit\ue9 dans de
nombreux cas. Personnes avec l\u2019hypertension non trait\ue9e ou
non contr\uf4l\ue9e souvent risquent de d\ue9velopper
complications directement associ\ue9es \ue0 la maladie. Laiss\ue9
ventriculaire hypertrophie (LVH) a \ue9t\ue9 d\ue9montr\ue9 un
facteur de risque signifi catif pour les effets n\ue9gatifs
r\ue9sultats tant chez les patients atteints de l\u2019hypertension
et de la population g\ue9n\ue9rale. Nous avons a enqu\ueat\ue9
sur la pr\ue9valence et le mod\ue8le de LVH dans un trait\ue9
hypertendues population au University College Hospital, \ue0
l\u2019aide Ibadan, Nigeria non-hypertendues des sujets comme
contr\uf4le. conception et la confi guration: A \ue9ventuel
\ue9tude d\u2019observation effectu\ue9e \ue0 la University
College Hospital, Ibadan, Nigeria. m\ue9thodes: Patients avaient six
visites o\uf9 au moins un sang mesure de pression a \ue9t\ue9
enregistr\ue9e pour chaque sujet hypertendues et moyenne
calcul\ue9s s\ue9par\ue9ment pour SBP et DBP. Les valeurs
obtenues ont \ue9t\ue9 utilis\ue9es pour stratifi cation des
sujets dans l\u2019hypertension contr\uf4l\ue9e et
incontr\uf4l\ue9e. Sujets ont \ue9galement echocardiograms pour
d\ue9terminer leur masse ventriculaire gauche. r\ue9sultats: LVH a
\ue9t\ue9 trouv\ue9 en 14(18.2%) de la groupe normotensive,
40(20.8%) de groupe de hypertendues non contr\uf4l\ue9es et
14(24.1%) de hypertendues contr\uf4l\ue9e groupe lorsque
quitt\ue9 masse ventriculaire (LVM) a \ue9t\ue9 index\ue9e
\ue0 corps surface (BSA). Lorsque LVM a \ue9t\ue9 index\ue9
\ue0 hauteur, laiss\ue9 ventriculaire hypertrophie a \ue9t\ue9
trouv\ue9 dans aucun du groupe normotensive, bien qu\u2019il a
\ue9t\ue9 constat\ue9 pr\ue9sents dans les 43(22.4%) et
14(24.1%) de hypertendues non ma\ueetris\ue9e et
contr\uf4l\ue9e groupes respectivement. \uc9tait de
diff\ue9rence signifi cative dans la pr\ue9valence de la LVH
d\ue9tect\ue9s uniquement lorsque LVM a \ue9t\ue9 index\ue9
\ue0 hauteur alone. conclusion: clinique art\ue9rielle est un moyen
ineffi cace de mesurer le contr\uf4le de BP. Ainsi en sujet
hypertendues apparemment contr\uf4l\ue9e bas\ue9e sur la pression
art\ue9rielle de bureau, des changements structurels cardiaques
restent malgr\ue9 th\ue9rapie antihypertensive. Cette population
est toujours \ue0 risque de maladies cardiovasculaires
\ue9v\ue9nements
Echocardiographic partition values and prevalence of left ventricular hypertrophy in hypertensive Nigerians
BACKGROUND: Left ventricular hypertrophy (LVH) is a well known independent risk factor for cardiovascular events. It has been shown that combination of left ventricular mass (LVM) and relative wall thickness (RWT) can be used to identify different forms of left ventricular (LV) geometry. Prospective studies have shown that LV geometric patterns have prognostic implications, with the worst prognosis associated with concentric hypertrophy. The methods for the normalization or indexation of LVM have also recently been shown to confer some prognostic value especially in obese population. We sought to determine the prevalence of echocardiographic lLVH using eight different and published cut-off or threshold values in hypertensive subjects seen in a developing country's tertiary centre. METHODS: Echocardiography was performed in four hundred and eighty consecutive hypertensive subjects attending the cardiology clinic of the University college Hospital Ibadan, Nigeria over a two-year period. RESULTS: Complete data was obtained in 457 (95.2%) of the 480 subjects (48.6% women). The prevalence of LVH ranged between 30.9–56.0%. The highest prevalence was when LVM was indexed to the power of 2.7 with a partition value of 49.2 g/ht(2.7 )in men and 46.7 g/ht(2.7 )in women. The lowest prevalence was observed when LVM was indexed to body surface area (BSA) and a partition value of 125 g/m(2 )was used for both sexes. Abnormal LV geometry was present in 61.1%–74.0% of our subjects and commoner in women. CONCLUSION: The prevalence of LVH hypertensive patients is strongly dependent on the cut-off value used to define it. Large-scale prospective study will be needed to determine the prognostic implications of the different LV geometry in native Africans
Characterisation of heart failure with normal ejection fraction in a tertiary hospital in Nigeria
<p>Abstract</p> <p>Background</p> <p>The study aimed to determine the frequency and characteristics of heart failure with normal EF in a native African population with heart failure.</p> <p>Methods</p> <p>It was a hospital cohort study. Subjects were 177 consecutive individuals with heart failure and ninety apparently normal control subjects. All the subjects underwent transthoracic echocardiography. The group with heart failure was further subdivided into heart failure with normal EF (EF ≥ 50) (HFNEF) and heart failure with low EF(EF <50)(HFLEF).</p> <p>Results</p> <p>The subjects with heart failure have a mean age of 52.3 ± 16.64 years vs 52.1 ± 11.84 years in the control subjects; p = 0.914. Other baseline characteristics except blood pressure parameters and height were comparable between the group with heart failure and the control subjects. The frequency of HFNEF was 39.5%. Compared with the HFLEF group, the HFNEF group have a smaller left ventricular diameter (in diastole and systole): (5.2 ± 1.22 cm vs 6.2 ± 1.39 cm; p < 0.0001 and 3.6 ± 1.24 cm vs 5.4 ± 1.35 cm;p < 0.0001) respectively, a higher relative wall thickness and deceleration time of the early mitral inflow velocity: (0.4 ± 0.12 vs 0.3 ± 0.14 p < 0.0001 and 149.6 ± 72.35 vs 110.9 ± 63.40 p = 0.001) respectively.</p> <p>The two groups with heart failure differed significantly from the control subjects in virtually all echocardiographic measurements except aortic root diameter, LV posterior wall thickness(HFLEF), and late mitral inflow velocity(HFNEF). HFNEF accounted for 70(39.5%) of cases of heart failure in this study.</p> <p>Hypertension is the underlying cardiovascular disease in 134(75.7%) of the combined heart failure population, 58 (82.9%) of the subjects with HFNEF group and 76(71%) of the HFLEF group. Females accounted for 44 (62.9%) of the subjects with HFNEF against 42(39.3%) in the HFLEF group (p = 0.002).</p> <p>Conclusion</p> <p>The frequency of heart failure with normal EF in this native African cohort with heart failure is comparable with the frequency in other populations. These groups of patients are more likely female, hypertensive with concentric pattern of left ventricular hypertrophy.</p
Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017
© 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license Background: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of “leaving no one behind”, it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990–2017, projected indicators to 2030, and analysed global attainment. Methods: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0–100, with 0 as the 2·5th percentile and 100 as the 97·5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings: The global median health-related SDG index in 2017 was 59·4 (IQR 35·4–67·3), ranging from a low of 11·6 (95% uncertainty interval 9·6–14·0) to a high of 84·9 (83·1–86·7). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation: The GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains—curative interventions in the case of NCDs—towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions—or inaction—today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030. Funding: Bill & Melinda Gates Foundation
Global, regional, and national age-sex-specific mortality and life expectancy, 1950-2017 : a systematic analysis for the Global Burden of Disease Study 2017
Background Assessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally. Methods The GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systetns, sample registration systetns, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specific mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in different components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950. Findings Globally, 18.7% (95% uncertainty interval 18.4-19.0) of deaths were registered in 1950 and that proportion has been steadily increasing since, with 58.8% (58.2-59.3) of all deaths being registered in 2015. At the global level, between 1950 and 2017, life expectancy increased from 48.1 years (46.5-49.6) to 70.5 years (70.1-70.8) for men and from 52.9 years (51.7-54.0) to 75.6 years (75.3-75.9) for women. Despite this overall progress, there remains substantial variation in life expectancy at birth in 2017, which ranges from 49.1 years (46.5-51.7) for men in the Central African Republic to 87.6 years (86.9-88.1) among women in Singapore. The greatest progress across age groups was for children younger than 5 years; under-5 mortality dropped from 216.0 deaths (196.3-238.1) per 1000 livebirths in 1950 to 38.9 deaths (35.6-42.83) per 1000 livebirths in 2017, with huge reductions across countries. Nevertheless, there were still 5.4 million (5.2-5.6) deaths among children younger than 5 years in the world in 2017. Progress has been less pronounced and more variable for adults, especially for adult tnales, who had stagnant or increasing mortality rates in several countries. The gap between male and female life expectancy between 1950 and 2017, while relatively stable at the global level, shows distinctive patterns across super-regions and has consistently been the largest in central Europe, eastern Europe, and central Asia, and smallest in south Asia. Performance was also variable across countries and time in observed mortality rates compared with those expected on the basis of development. Interpretation This analysis of age-sex-specific mortality shows that there are remarkably complex patterns in population mortality across countries. The findings of this study highlight global successes, such as the large decline in under-5 mortality, which reflects significant local, national, and global commitment and investment over several decades. However, they also bring attention to mortality patterns that are a cause for concern, particularly among adult men and, to a lesser extent, wotnen, whose mortality rates have stagnated in many countries over the time period of this study, and in some cases are increasing. Copyright C) 2018 The Author(s). Published by Elsevier Ltd.Peer reviewe
Global, regional, and national age-sex-specific mortality and life expectancy, 1950-2017: A systematic analysis for the Global Burden of Disease Study 2017
© 2018 The Author(s). Background: Assessments of age-specifc mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Afairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally. Methods: The GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systems, sample registration systems, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specifc mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in diferent components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950. Findings: Globally, 18·7% (95% uncertainty interval 18·4-19·0) of deaths were registered in 1950 and that proportion has been steadily increasing since, with 58·8% (58·2-59·3) of all deaths being registered in 2015. At the global level, between 1950 and 2017, life expectancy increased from 48·1 years (46·5-49·6) to 70·5 years (70·1-70·8) for men and from 52·9 years (51·7-54·0) to 75·6 years (75·3-75·9) for women. Despite this overall progress, there remains substantial variation in life expectancy at birth in 2017, which ranges from 49·1 years (46·5-51·7) for men in the Central African Republic to 87·6 years (86·9-88·1) among women in Singapore. The greatest progress across age groups was for children younger than 5 years; under-5 mortality dropped from 216·0 deaths (196·3-238·1) per 1000 livebirths in 1950 to 38·9 deaths (35·6-42·83) per 1000 livebirths in 2017, with huge reductions across countries. Nevertheless, there were still 5·4 million (5·2-5·6) deaths among children younger than 5 years in the world in 2017. Progress has been less pronounced and more variable for adults, especially for adult males, who had stagnant or increasing mortality rates in several countries. The gap between male and female life expectancy between 1950 and 2017, while relatively stable at the global level, shows distinctive patterns across super-regions and has consistently been the largest in central Europe, eastern Europe, and central Asia, and smallest in south Asia. Performance was also variable across countries and time in observed mortality rates compared with those expected on the basis of development. Interpretation: This analysis of age-sex-specifc mortality shows that there are remarkably complex patterns in population mortality across countries. The fndings of this study highlight global successes, such as the large decline in under-5 mortality, which refects signifcant local, national, and global commitment and investment over several decades. However, they also bring attention to mortality patterns that are a cause for concern, particularly among adult men and, to a lesser extent, women, whose mortality rates have stagnated in many countries over the time period of this study, and in some cases are increasing
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
© 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license 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. Funding: Bill & Melinda Gates Foundation
Meningococcus serogroup C clonal complex ST-10217 outbreak in Zamfara State, Northern Nigeria.
After the successful roll out of MenAfriVac, Nigeria has experienced sequential meningitis outbreaks attributed to meningococcus serogroup C (NmC). Zamfara State in North-western Nigeria recently was at the epicentre of the largest NmC outbreak in the 21st Century with 7,140 suspected meningitis cases and 553 deaths reported between December 2016 and May 2017. The overall attack rate was 155 per 100,000 population and children 5-14 years accounted for 47% (3,369/7,140) of suspected cases. The case fatality rate (CFR) among children 5-9 years was 10%, double that reported among adults ≥ 30 years (5%). NmC and pneumococcus accounted for 94% (172/184) and 5% (9/184) of the laboratory-confirmed cases, respectively. The sequenced NmC belonged to the ST-10217 clonal complex (CC). All serotyped pneumococci were PCV10 serotypes. The emergence of NmC ST-10217 CC outbreaks threatens the public health gains made by MenAfriVac, which calls for an urgent strategic action against meningitis outbreaks
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
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.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
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