Cirrhosis is responsible for substantial health and economic burden in the USA. Reducing this burden requires better understanding of how rates of cirrhosis mortality vary by race and ethnicity and ...by geographical location. This study describes rates and trends in cirrhosis mortality for five racial and ethnic populations in 3110 US counties from 2000 to 2019.
We estimated cirrhosis mortality rates by county, race and ethnicity, and year (2000–19) using previously validated small-area estimation methods, death registration data from the US National Vital Statistics System, and population data from the US National Center for Health Statistics. Five racial and ethnic populations were considered: American Indian or Alaska Native (AIAN), Asian or Pacific Islander (Asian), Black, Latino or Hispanic (Latino), and White. Cirrhosis mortality rate estimates were age-standardised using the age distribution from the 2010 US census as the standard. For each racial and ethnic population, estimates are presented for all counties with a mean annual population greater than 1000.
From 2000 to 2019, national-level age-standardised cirrhosis mortality rates decreased in the Asian (23·8% 95% uncertainty interval 19·6–27·8, from 9·4 deaths per 100 000 population 8·9–9·9 to 7·1 per 100 000 6·8–7·5), Black (22·8% 20·6–24·8, from 19·8 per 100 000 19·4–20·3 to 15·3 per 100 000 15·0–15·6), and Latino (15·3% 13·3–17·3, from 26·3 per 100 000 25·6–27·0 to 22·3 per 100 000 21·8–22·8) populations and increased in the AIAN (39·3% 32·3–46·4, from 45·6 per 100 000 40·6–50·6 to 63·5 per 100 000 57·2–70·2 in 2000 and 2019, respectively) and White (25·8% 24·2–27·3, from 14·7 deaths per 100 000 14·6–14·9 to 18·5 per 100 000 18·4–18·7) populations. In all years, cirrhosis mortality rates were lowest among the Asian population, highest among the AIAN population, and higher in males than females for each racial and ethnic population. The degree of heterogeneity in county-level cirrhosis mortality rates varied by racial and ethnic population, with the narrowest IQR in the Asian population (median 8·0 deaths per 100 000, IQR 6·4–10·4) and the widest in the AIAN population (55·1, 30·3–78·8). Cirrhosis mortality increased over the study period in almost all counties for the White (2957 96·9% of 3051 counties) and AIAN (421 88·8% of 474) populations, but in a smaller proportion of counties for the Asian, Black, and Latino populations. For all racial and ethnic populations, cirrhosis mortality rates increased in more counties between 2000 and 2015 than between 2015 and 2019.
Cirrhosis mortality increased nationally and in many counties from 2000 to 2019. Although the magnitude of racial and ethnic disparities decreased in some places, disparities nonetheless persisted, and mortality remained high in many locations and communities. Our findings underscore the need to implement targeted and locally tailored programmes and policies to reduce the burden of cirrhosis at both the national and local level.
US National Institutes of Health (Intramural Research Program, National Institute on Minority Health and Health Disparities; National Heart, Lung, and Blood Institute; Intramural Research Program, National Cancer Institute; National Institute on Aging; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Office of Disease Prevention; and Office of Behavioral and Social Sciences Research).
Globally, countries are increasingly prioritizing the reduction of health inequalities and provision of universal health coverage. While national benchmarking has become more common, such work at ...subnational levels is rare. The timely and rigorous measurement of local levels and trends in key health interventions and outcomes is vital to identifying areas of progress and detecting early signs of stalled or declining health system performance. Previous studies have yet to provide a comprehensive assessment of Uganda's maternal and child health (MCH) landscape at the subnational level.
By triangulating a number of different data sources - population censuses, household surveys, and administrative data - we generated regional estimates of 27 key MCH outcomes, interventions, and socioeconomic indicators from 1990 to 2011. After calculating source-specific estimates of intervention coverage, we used a two-step statistical model involving a mixed-effects linear model as an input to Gaussian process regression to produce regional-level trends. We also generated national-level estimates and constructed an indicator of overall intervention coverage based on the average of 11 high-priority interventions.
National estimates often veiled large differences in coverage levels and trends across Uganda's regions. Under-5 mortality declined dramatically, from 163 deaths per 1,000 live births in 1990 to 85 deaths per 1,000 live births in 2011, but a large gap between Kampala and the rest of the country persisted. Uganda rapidly scaled up a subset of interventions across regions, including household ownership of insecticide-treated nets, receipt of artemisinin-based combination therapies among children under 5, and pentavalent immunization. Conversely, most regions saw minimal increases, if not actual declines, in the coverage of indicators that required multiple contacts with the health system, such as four or more antenatal care visits, three doses of oral polio vaccine, and two doses of intermittent preventive therapy during pregnancy. Some of the regions with the lowest levels of overall intervention coverage in 1990, such as North and West Nile, saw marked progress by 2011; nonetheless, sizeable disparities remained between Kampala and the rest of the country. Countrywide, overall coverage increased from 40% in 1990 to 64% in 2011, but coverage in 2011 ranged from 57% to 70% across regions.
The MCH landscape in Uganda has, for the most part, improved between 1990 and 2011. Subnational benchmarking quantified the persistence of geographic health inequalities and identified regions in need of additional health systems strengthening. The tracking and analysis of subnational health trends should be conducted regularly to better guide policy decisions and strengthen responsiveness to local health needs.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Achieving universal health coverage and reducing health inequalities are primary goals for an increasing number of health systems worldwide. Timely and accurate measurements of levels and trends in ...key health indicators at local levels are crucial to assess progress and identify drivers of success and areas that may be lagging behind.
We generated estimates of 17 key maternal and child health indicators for Zambia's 72 districts from 1990 to 2010 using surveys, censuses, and administrative data. We used a three-step statistical model involving spatial-temporal smoothing and Gaussian process regression. We generated estimates at the national level for each indicator by calculating the population-weighted mean of the district values and calculated composite coverage as the average of 10 priority interventions.
National estimates masked substantial variation across districts in the levels and trends of all indicators. Overall, composite coverage increased from 46% in 1990 to 73% in 2010, and most of this gain was attributable to the scale-up of malaria control interventions, pentavalent immunization, and exclusive breastfeeding. The scale-up of these interventions was relatively equitable across districts. In contrast, progress in routine services, including polio immunization, antenatal care, and skilled birth attendance, stagnated or declined and exhibited large disparities across districts. The absolute difference in composite coverage between the highest-performing and lowest-performing districts declined from 37 to 26 percentage points between 1990 and 2010, although considerable variation in composite coverage across districts persisted.
Zambia has made marked progress in delivering maternal and child health interventions between 1990 and 2010; nevertheless, substantial variations across districts and interventions remained. Subnational benchmarking is important to identify these disparities, allowing policymakers to prioritize areas of greatest need. Analyses such as this one should be conducted regularly and feed directly into policy decisions in order to increase accountability at the local, regional, and national levels.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The article estimates age-standardized mortality rates by US country from 29 cancers. Cancer mortality declined overall in the United States between 1980 and 2014. Over this same period, there were ...important changes in trends, patterns and differences in cancer mortality among US countries.
There are persistent disparities in stomach cancer mortality among racial–ethnic groups in the USA, but the extent to which these patterns vary geographically is not well understood. This analysis ...estimated age-standardised mortality for five racial–ethnic groups, in 3110 USA counties over 20 years, to describe spatial–temporal variations in stomach cancer mortality and disparities between racial–ethnic groups.
Redistribution methods for insufficient cause of death codes and validated small area estimation methods were applied to death registration data from the US National Vital Statistics System and population data from the US National Center for Health Statistics to estimate annual stomach cancer mortality rates. Estimates were stratified by county and racial–ethnic group (non-Latino and non-Hispanic NL American Indian or Alaska Native AIAN, NL Asian or Pacific Islander Asian, NL Black Black, Latino or Hispanic Latino, and NL White White) from 2000 to 2019. Estimates were corrected for misreporting of racial–ethnic group on death certificates using published misclassification ratios. We masked (ie, did not display) estimates for county and racial–ethnic group combinations with a mean annual population of less than 1000; thus, we report estimates for 3079 (of 3110) counties for the total population, and 474, 667, 1488, 1478, and 3051 counties for the AIAN, Asian, Black, Latino, and White populations, respectively.
Between 2000 and 2019, national age-standardised stomach cancer mortality was lowest among the White population in every year. Nationally, stomach cancer mortality declined for all racial–ethnic groups across this time period, with the most rapid declines occurring among the Asian (percent decline 48.3% 45.1–51.1) and Black populations (42.6% 40.2–44.6). Mortality among the other racial–ethnic groups declined more moderately, decreasing by 36.7% (35.3–38.1), 35.1% (32.2–37.7), and 31.6% (23.9–38.0) among the White, Latino, and AIAN populations, respectively. Similar patterns were observed at the county level, although with wide geographic variation. In 2019, a majority of counties had higher mortality rates among minoritised racial–ethnic populations compared to the White population: 81.1% (377 of 465 counties with unmasked estimates for both racial–ethnic groups) among the AIAN population, 88.2% (1295 of 1469) among the Latino population, 99.4% (663 of 667) among the Asian population, and 99.9% (1484 of 1486) among the Black population. However, the size of these disparities ranged widely across counties, with the largest range from 0.3 to 17.1 among the AIAN population.
Stomach cancer mortality has decreased substantially across populations and geographies in the USA. However, disparities in stomach cancer mortality among racial–ethnic groups are widespread and have persisted over the last two decades. Local-level data are crucial to understanding the scope of this unequal burden among minoritised groups in the USA.
National Institute on Minority Health and Health Disparities; National Heart, Lung, and Blood Institute; National Cancer Institute; National Institute on Aging; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Office of Disease Prevention; and Office of Behavioral and Social Sciences Research, National Institutes of Health (contract #75N94019C00016).
Fall-related mortality has increased rapidly over the past two decades in the USA, but the extent to which mortality varies across racial and ethnic populations, counties, and age groups is not well ...understood. The aim of this study was to estimate age-standardised mortality rates due to falls by racial and ethnic population, county, and age group over a 20-year period.
Redistribution methods for insufficient cause of death codes and validated small-area estimation methods were applied to death registration data from the US National Vital Statistics System and population data from the US National Center for Health Statistics to estimate annual fall-related mortality. Estimates from 2000 to 2019 were stratified by county (n=3110) and five mutually exclusive racial and ethnic populations: American Indian or Alaska Native (AIAN), Asian or Pacific Islander (Asian), Black, Latino or Hispanic (Latino), and White. Estimates were corrected for misreporting of race and ethnicity on death certificates using published misclassification ratios. We masked (ie, did not display) estimates for county and racial and ethnic population combinations with a mean annual population of less than 1000. Age-standardised mortality is presented for all ages combined and for age groups 20–64 years (younger adults) and 65 years and older (older adults).
Nationally, in 2019, the overall age-standardised fall-related mortality rate for the total population was 13·4 deaths per 100 000 population (95% uncertainty interval 13·3–13·6), an increase of 65·3% (61·9–68·8) from 8·1 deaths per 100 000 (8·0–8·3) in 2000, with the largest increases observed in older adults. Fall-related mortality at the national level was highest across all years in the AIAN population (in 2019, 15·9 deaths per 100 000 population 95% uncertainty interval 14·0–18·2) and White population (14·8 deaths per 100 000 14·6–15·0), and was about half as high among the Latino (8·7 deaths per 100 000 8·3–9·0), Black (8·1 deaths per 100 000 7·9–8·4), and Asian (7·5 deaths per 100 000 7·1–7·9) populations. The disparities between racial and ethnic populations varied widely by age group, with mortality among younger adults highest for the AIAN population and mortality among older adults highest for the White population. The national-level patterns were observed broadly at the county level, although there was considerable spatial variation across ages and racial and ethnic populations. For younger adults, among almost all counties with unmasked estimates, there was higher mortality in the AIAN population than in all other racial and ethnic populations, while there were pockets of high mortality in the Latino population, particularly in the Mountain West region. For older adults, mortality was particularly high in the White population within clusters of counties across states including Florida, Minnesota, and Wisconsin.
Age-standardised mortality due to falls increased over the study period for each racial and ethnic population and almost every county. Wide variation in mortality across geography, age, and race and ethnicity highlights areas and populations that might benefit most from efficacious fall prevention interventions as well as additional prevention research.
US National Institutes of Health (Intramural Research Program, National Institute on Minority Health and Health Disparities; National Heart, Lung, and Blood Institute; Intramural Research Program, National Cancer Institute; National Institute on Aging; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Office of Disease Prevention; and Office of Behavioral and Social Sciences Research).
The article demonstrates the use of a novel method for country-level estimation and to estimate annual mortality rates by US country for 21 mutually exclusive causes of death from 1980 through 2014. ...In the analysis of US cause-specific country-level mortality rates from 1980 through 2014, there were large between-country differences for every cause of death, although geographics pattern varied substantially by cause of death. The approach to country-level analyses with small area models used has the potential to provide novel insights into US disease-specific mortality time trends and their difference across geographic regions.
Estimates of under-5 mortality at the national level for countries without high-quality vital registration systems are routinely derived from birth history data in censuses and surveys. Subnational ...or stratified analyses of under-5 mortality could also be valuable, but the usefulness of under-5 mortality estimates derived from birth histories from relatively small samples of women is not known. We aim to assess the magnitude and direction of error that can be expected for estimates derived from birth histories with small samples of women using various analysis methods.
We perform a data-based simulation study using Demographic and Health Surveys. Surveys are treated as populations with known under-5 mortality, and samples of women are drawn from each population to mimic surveys with small sample sizes. A variety of methods for analyzing complete birth histories and one method for analyzing summary birth histories are used on these samples, and the results are compared to corresponding true under-5 mortality. We quantify the expected magnitude and direction of error by calculating the mean error, mean relative error, mean absolute error, and mean absolute relative error.
All methods are prone to high levels of error at the smallest sample size with no method performing better than 73% error on average when the sample contains 10 women. There is a high degree of variation in performance between the methods at each sample size, with methods that contain considerable pooling of information generally performing better overall. Additional stratified analyses suggest that performance varies for most methods according to the true level of mortality and the time prior to survey. This is particularly true of the summary birth history method as well as complete birth history methods that contain considerable pooling of information across time.
Performance of all birth history analysis methods is extremely poor when used on very small samples of women, both in terms of magnitude of expected error and bias in the estimates. Even with larger samples there is no clear best method to choose for analyzing birth history data. The methods that perform best overall are the same methods where performance is noticeably different at different levels of mortality and lengths of time prior to survey. At the same time, methods that perform more uniformly across levels of mortality and lengths of time prior to survey also tend to be among the worst performing overall.
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