Estimating progress towards meeting women's contraceptive needs in 185 countries: A Bayesian hierarchical modelling study.

BACKGROUND: Expanding access to contraception and ensuring that need for family planning is satisfied are essential for achieving universal access to reproductive healthcare services, as called for in the 2030 Agenda for Sustainable Development. Monitoring progress towards these outcomes is well established for women of reproductive age (15-49 years) who are married or in a union (MWRA). For those who are not, limited data and variability in data sources and indicator definitions make monitoring challenging. To our knowledge, this study is the first to provide data and harmonised estimates that enable monitoring for all women of reproductive age (15-49 years) (WRA), including unmarried women (UWRA). We seek to quantify the gaps that remain in meeting family-planning needs among all WRA. METHODS AND FINDINGS: In a systematic analysis, we compiled a comprehensive dataset of family-planning indicators among WRA from 1,247 nationally representative surveys. We used a Bayesian hierarchical model with country-specific time trends to estimate these indicators, with 95% uncertainty intervals (UIs), for 185 countries. We produced estimates from 1990 to 2019 and projections from 2019 to 2030 of contraceptive prevalence and unmet need for family planning among MWRA, UWRA, and all WRA, taking into account the changing proportions that were married or in a union. The model accounted for differences in the prevalence of sexual activity among UWRA across countries. Among 1.9 billion WRA in 2019, 1.11 billion (95% UI 1.07-1.16) have need for family planning; of those, 842 million (95% UI 800-893) use modern contraception, and 270 million (95% UI 246-301) have unmet need for modern methods. Globally, UWRA represented 15.7% (95% UI 13.4%-19.4%) of all modern contraceptive users and 16.0% (95% UI 12.9%-22.1%) of women with unmet need for modern methods in 2019. The proportion of the need for family planning satisfied by modern methods, Sustainable Development Goals (SDG) indicator 3.7.1, was 75.7% (95% UI 73.2%-78.0%) globally, yet less than half of the need for family planning was met in Middle and Western Africa. Projections to 2030 indicate an increase in the number of women with need for family planning to 1.19 billion (95% UI 1.13-1.26) and in the number of women using modern contraception to 918 million (95% UI 840-1,001). The main limitations of the study are as follows: (i) the uncertainty surrounding estimates for countries with little or no data is large; and (ii) although some adjustments were made, underreporting of contraceptive use and needs is likely, especially among UWRA. CONCLUSIONS: In this study, we observed that large gaps remain in meeting family-planning needs. The projected increase in the number of women with need for family planning will create challenges to expand family-planning services fast enough to fulfil the growing need. Monitoring of family-planning indicators for all women, not just MWRA, is essential for accurately monitoring progress towards universal access to sexual and reproductive healthcare services-including family planning-by 2030 in the SDG era with its emphasis on 'leaving no one behind.'

Bayesian population reconstruction of female populations for less developed and more developed countries.

We show that Bayesian population reconstruction, a recent method for estimating past populations by age, works for data of widely varying quality. Bayesian reconstruction simultaneously estimates age-specific population counts, fertility rates, mortality rates, and net international migration flows from fragmentary data, while formally accounting for measurement error. As inputs, Bayesian reconstruction uses initial bias-reduced estimates of standard demographic variables. We reconstruct the female populations of three countries: Laos, a country with little vital registration data where population estimation depends largely on surveys; Sri Lanka, a country with some vital registration data; and New Zealand, a country with a highly developed statistical system and good quality vital registration data. In addition, we extend the method to countries without censuses at regular intervals. We also use it to assess the consistency of results between model life tables and available census data, and hence to compare different model life table systems.

Evaluation of seasonality in the diagnosis of acute myeloid leukaemia among adults in the United States, 1992-2008.

Recent studies have suggested seasonal variation in the diagnosis of acute myeloid leukaemia (AML), and the aetiological role seasonal factors may play in this group of haematological neoplasms remains unclear. We evaluated potential seasonality of AML diagnosis among adults. Cases included were ascertained from the Surveillance, Epidemiology, and End Results (SEER) 13 registries from 1992-2008. Chi-square analysis for heterogeneity and multiple Poisson regression using parametric harmonic modelling and bootstrap testing were used to detect possible monthly variation. Months of peak diagnoses were December and January, although some variation was present by sex and age. Heterogeneity across months was statistically significant (P < 0·001). In stratified analyses, monthly variation was detected only among males (P = 0·009) and in cases aged 65 years and older (P = 0·031). Poisson regression found no seasonal effect among all cases when fit to the sinusoidal model (P = 0·110). However, similar variation among males (P = 0·009) and cases aged 65 years and older (P = 0·018) was present. There is growing evidence of seasonality in AML diagnosis, particularly among older persons and men. Investigation of specific seasonal risk factors would be informative in explaining the aetiology behind the observed variation.

Setting Health Targets Using Information from Probabilistic Projections: A Research Brief on an Application to Contraceptive Coverage.

Broad and aspirational targets to meet health service needs are useful for advocacy, but setting measurable, time-defined targets for accelerated yet feasible progress is necessary for national monitoring and planning purposes. Information from probabilistic projections of health outcomes and service coverage can be used to set country-specific targets that reflect different starting points and rates of change. We show the utility of this approach in an application to contraceptive coverage in 131 low- and middle-income countries (LMICs) and the related cost and impact of different coverage scenarios. We use the sustainable development goal (SDG) indicator of the proportion of women who have their need for family planning satisfied with modern contraception. The results show that accelerated progress targets would collectively result in 83% of the need satisfied in 2030 for LMICs, which is 5% points higher than the projected level based on the current pace of progress. This translated into 41 million fewer women with an unmet need for modern methods and 14 million fewer unintended pregnancies. Annual direct costs would be $480 million more in 2030 to support contraceptive services compared with costs in 2030 based on the current pace of progress. As governments plan and budget for expanded health service coverage, information from probabilistic projections can guide them in setting measurable, ambitious yet realistic targets that are relevant to their particular contexts. Supplementary Information: The online version contains supplementary material available at 10.1007/s11113-023-09766-2.

Contraceptive use and needs among adolescent women aged 15-19: Regional and global estimates and projections from 1990 to 2030 from a Bayesian hierarchical modelling study.

Expanding access to contraception and ensuring that need for family planning is satisfied are essential for achieving universal access to reproductive healthcare services, as called for in the 2030 Agenda for Sustainable Development. To quantify the gaps that remain in meeting needs among adolescents, this study provides a harmonised data set and global estimates and projections of family planning indicators for adolescents aged 15-19 years. We compiled a comprehensive dataset of family-planning indicators among women aged 15-19 from 754 nationally representative surveys. We used a Bayesian hierarchical model with country-specific annual trends to estimate contraceptive prevalence and unmet need for family planning, with 95% uncertainty intervals (UIs), for 185 countries, taking into account changes in proportions married or in a union and differences in sexual activity among unmarried women across countries. Among 300 million women aged 15-19 years in 2019, 29.8 million (95% UI 24.6-41.7) use any contraception, and 15.0 million (95% UI 12.1-29.2) have unmet need for family planning. Population growth and the postponement of marriage influence trends in the absolute number of adolescents using contraception or experiencing unmet need. Large gaps remain in meeting family-planning needs among adolescents. The proportion of the need satisfied by modern methods, Sustainable Development Goals (SDG) indicator 3.7.1, was 59.2% (95% UI 44.8-67.2) globally among adolescents, lower compared to 75.7% (95% UI 73.2%-78.0%) among all women age 15-49 years. It was less than one half of adolescents in need in Western Asia and Northern Africa (38.7%, 95%UI = 20.9-56.5), Central and Southern Asia (43.5%, 95%UI = 36.6-52.3), and sub-Saharan Africa (45.6%, 95%UI = 42.2-49.0). The main limitations of the study are: (i) the uncertainty surrounding estimates for countries with limited or biased data is large; and (ii) underreporting of contraceptive use and needs is likely, especially among unmarried adolescents.

Pharmacokinetics of metformin in patients with chronic kidney disease stage 4 and metformin-naïve type 2 diabetes.

The pharmacokinetics of metformin therapy in patients with chronic kidney disease stage 4 (CKD-4) were studied using data from the largest Phase I consecutive cohort trial yet performed in this population. Eighteen metformin-naïve men and women with Type 2 Diabetes and creatinine clearance (CrCl) in the range 18-49 mL/min (eGFR 15-29 mL/min/1.73 m2) were allocated to daily immediate-release metformin of 250 mg, 500 mg, or 1000 mg. A first-dose profile and trough concentrations for 4 weeks were taken on all patients. Pharmacokinetic (PK) parameters were estimated by fitting a first-order compartment model with absorption in a peripheral compartment to concentrations measured 24 hours post-first dose. Single-dose PK parameters time to maximum concentration (tmax) and maximum concentration (Cmax) were consistent with previous observations in patients with normal renal function (healthy and diabetic), as was the association between CrCl and apparent total oral clearance (Cl/F). However, patients with a CrCl below 32 mL/min had trough concentrations that were consistently above the steady-state minimum implied by the population PK model. This suggests the model may not apply to patients with CrCl below 32 mL/min. Metformin in doses of 500-1000 mg/day could be taken by CKD-4 patients. However, the single-compartment model breaks down as CrCl declines below 32 mL/min suggesting that metformin levels should be monitored regularly in progressive stage 4 CKD.

Bayesian Reconstruction of Two-Sex Populations by Age: Estimating Sex Ratios at Birth and Sex Ratios of Mortality.

The original version of Bayesian reconstruction, a method for estimating age-specific fertility, mortality, migration and population counts of the recent past with uncertainty, produced estimates for female-only populations. Here we show how two-sex populations can be similarly reconstructed and probabilistic estimates of various sex ratio quantities obtained. We demonstrate the method by reconstructing the populations of India from 1971 to 2001, Thailand from 1960 to 2000, and Laos from 1985 to 2005. We found evidence that in India, sex ratio at birth exceeded its conventional upper limit of 1.06, and, further, increased over the period of study, with posterior probability above 0.9. In addition, almost uniquely, we found evidence that life expectancy at birth (e0) was lower for females than for males in India (posterior probability for 1971-1976 equal to 0.79), although there was strong evidence for a narrowing of the gap through to 2001. In both Thailand and Laos, we found strong evidence for the more usual result that e0 was greater for females and, in Thailand, that the difference increased over the period of study.

Reconstructing Past Populations With Uncertainty From Fragmentary Data.

Current methods for reconstructing human populations of the past by age and sex are deterministic or do not formally account for measurement error. We propose a method for simultaneously estimating age-specific population counts, fertility rates, mortality rates, and net international migration flows from fragmentary data that incorporates measurement error. Inference is based on joint posterior probability distributions that yield fully probabilistic interval estimates. It is designed for the kind of data commonly collected in modern demographic surveys and censuses. Population dynamics over the period of reconstruction are modeled by embedding formal demographic accounting relationships in a Bayesian hierarchical model. Informative priors are specified for vital rates, migration rates, population counts at baseline, and their respective measurement error variances. We investigate calibration of central posterior marginal probability intervals by simulation and demonstrate the method by reconstructing the female population of Burkina Faso from 1960 to 2005. Supplementary materials for this article are available online and the method is implemented in the R package "popReconstruct."