Prevalence of Age-Related Macular Degeneration in the US in 2019.

Importance: Age-related macular degeneration (AMD) is a leading cause of vision loss and blindness. AMD prevalence has not been estimated for the US in over a decade and early-stage AMD prevalence estimates are scarce and inconsistently measured. Objective: To produce estimates of early- and late-stage AMD prevalence overall and by age, gender, race and ethnicity, county, and state. Design, Setting, and Participants: The study team conducted a bayesian meta-regression analysis of relevant data sources containing information on the prevalence of AMD among different population groups in the US. Data Sources: We included data from the American Community Survey (2019), the National Health and Nutrition Examination Survey (2005-2008), US Centers for Medicare & Medicaid Services claims for fee-for-service beneficiaries (2018), and population-based studies (2004-2016). Study Selection: We included all relevant data from the US Centers for Disease Control and Prevention's Vision and Eye Health Surveillance System. Data Extraction and Synthesis: The prevalence of early- and late-stage AMD was estimated and stratified when possible by factors including county, age group, gender, and race and ethnicity. Data analysis occurred from June 2021 to April 2022. Main Outcomes or Measures: The prevalence of early- (defined as retinal pigment epithelium abnormalities or the presence of drusen 125 or more microns in diameter in either eye) and late-stage (defined as choroidal neovascularization and/or geographic atrophy in either eye) manifestations of AMD. Results: This study used data from nationally representative and local population-based studies that represent the populations in which they were conducted. For 2019, we estimated that there were 18.34 million people 40 years and older (95% uncertainty interval [UI], 15.30-22.03) living with early-stage AMD, corresponding to a crude prevalence rate of 11.64% (95% UI, 9.71-13.98). We estimated there were 1.49 million people 40 years and older (95% UI, 0.97-2.15) living with late-stage AMD, corresponding to a crude prevalence rate of 0.94% (95% UI, 0.62-1.36). Prevalence rates of early- and late-stage AMD varied by demographic characteristics and geography. Conclusions and Relevance: We estimated a higher prevalence of early-stage AMD and a similar prevalence of late-stage AMD as compared with earlier studies. State-level and county-level AMD estimates may help guide public health practice.

Prevalence of Visual Acuity Loss or Blindness in the US: A Bayesian Meta-analysis.

IMPORTANCE: Globally, more than 250 million people live with visual acuity loss or blindness, and people in the US fear losing vision more than memory, hearing, or speech. But it appears there are no recent empirical estimates of visual acuity loss or blindness for the US. OBJECTIVE: To produce estimates of visual acuity loss and blindness by age, sex, race/ethnicity, and US state. DATA SOURCES: Data from the American Community Survey (2017), National Health and Nutrition Examination Survey (1999-2008), and National Survey of Children's Health (2017), as well as population-based studies (2000-2013), were included. STUDY SELECTION: All relevant data from the US Centers for Disease Control and Prevention's Vision and Eye Health Surveillance System were included. DATA EXTRACTION AND SYNTHESIS: The prevalence of visual acuity loss or blindness was estimated, stratified when possible by factors including US state, age group, sex, race/ethnicity, and community-dwelling or group-quarters status. Data analysis occurred from March 2018 to March 2020. MAIN OUTCOMES OR MEASURES: The prevalence of visual acuity loss (defined as a best-corrected visual acuity greater than or equal to 0.3 logMAR) and blindness (defined as a logMAR of 1.0 or greater) in the better-seeing eye. RESULTS: For 2017, this meta-analysis generated an estimated US prevalence of 7.08 (95% uncertainty interval, 6.32-7.89) million people living with visual acuity loss, of whom 1.08 (95% uncertainty interval, 0.82-1.30) million people were living with blindness. Of this, 1.62 (95% uncertainty interval, 1.32-1.92) million persons with visual acuity loss are younger than 40 years, and 141 000 (95% uncertainty interval, 95 000-187 000) persons with blindness are younger than 40 years. CONCLUSIONS AND RELEVANCE: This analysis of all available data with modern methods produced estimates substantially higher than those previously published.

Fertility, mortality, migration, and population scenarios for 195 countries and territories from 2017 to 2100: a forecasting analysis for the Global Burden of Disease Study.

BACKGROUND: Understanding potential patterns in future population levels is crucial for anticipating and planning for changing age structures, resource and health-care needs, and environmental and economic landscapes. Future fertility patterns are a key input to estimation of future population size, but they are surrounded by substantial uncertainty and diverging methodologies of estimation and forecasting, leading to important differences in global population projections. Changing population size and age structure might have profound economic, social, and geopolitical impacts in many countries. In this study, we developed novel methods for forecasting mortality, fertility, migration, and population. We also assessed potential economic and geopolitical effects of future demographic shifts. METHODS: We modelled future population in reference and alternative scenarios as a function of fertility, migration, and mortality rates. We developed statistical models for completed cohort fertility at age 50 years (CCF50). Completed cohort fertility is much more stable over time than the period measure of the total fertility rate (TFR). We modelled CCF50 as a time-series random walk function of educational attainment and contraceptive met need. Age-specific fertility rates were modelled as a function of CCF50 and covariates. We modelled age-specific mortality to 2100 using underlying mortality, a risk factor scalar, and an autoregressive integrated moving average (ARIMA) model. Net migration was modelled as a function of the Socio-demographic Index, crude population growth rate, and deaths from war and natural disasters; and use of an ARIMA model. The model framework was used to develop a reference scenario and alternative scenarios based on the pace of change in educational attainment and contraceptive met need. We estimated the size of gross domestic product for each country and territory in the reference scenario. Forecast uncertainty intervals (UIs) incorporated uncertainty propagated from past data inputs, model estimation, and forecast data distributions. FINDINGS: The global TFR in the reference scenario was forecasted to be 1·66 (95% UI 1·33-2·08) in 2100. In the reference scenario, the global population was projected to peak in 2064 at 9·73 billion (8·84-10·9) people and decline to 8·79 billion (6·83-11·8) in 2100. The reference projections for the five largest countries in 2100 were India (1·09 billion [0·72-1·71], Nigeria (791 million [594-1056]), China (732 million [456-1499]), the USA (336 million [248-456]), and Pakistan (248 million [151-427]). Findings also suggest a shifting age structure in many parts of the world, with 2·37 billion (1·91-2·87) individuals older than 65 years and 1·70 billion (1·11-2·81) individuals younger than 20 years, forecasted globally in 2100. By 2050, 151 countries were forecasted to have a TFR lower than the replacement level (TFR <2·1), and 183 were forecasted to have a TFR lower than replacement by 2100. 23 countries in the reference scenario, including Japan, Thailand, and Spain, were forecasted to have population declines greater than 50% from 2017 to 2100; China's population was forecasted to decline by 48·0% (-6·1 to 68·4). China was forecasted to become the largest economy by 2035 but in the reference scenario, the USA was forecasted to once again become the largest economy in 2098. Our alternative scenarios suggest that meeting the Sustainable Development Goals targets for education and contraceptive met need would result in a global population of 6·29 billion (4·82-8·73) in 2100 and a population of 6·88 billion (5·27-9·51) when assuming 99th percentile rates of change in these drivers. INTERPRETATION: Our findings suggest that continued trends in female educational attainment and access to contraception will hasten declines in fertility and slow population growth. A sustained TFR lower than the replacement level in many countries, including China and India, would have economic, social, environmental, and geopolitical consequences. Policy options to adapt to continued low fertility, while sustaining and enhancing female reproductive health, will be crucial in the years to come. FUNDING: Bill & Melinda Gates Foundation.