The pandemic preterm paradox: A test of competing explanations.

Epidemiologists have long argued that side effects of the stress response include preterm birth. Research reports that fear of lethal infection stressed pregnant persons at the outset of the COVID-19 pandemic and that "shutdowns" and "social distancing" impeded access to social support and prenatal care. The decline in preterm births in high-income countries, including the United States (US), during the early months of the pandemic therefore poses a paradox for science. Explanations of this "pandemic preterm paradox" remain untested. We apply time-series modeling to data describing 80 monthly conception cohorts begun in the US from July 2013 through February 2020 to determine which of 3 explanations most parsimoniously explains the paradox. We infer that "prior loss," or the argument that an increase in spontaneous abortions and stillbirths depleted the population of fetuses at risk of preterm birth, best explains data currently available. We describe the implications of these results for public health practice.

Scarring In Utero: An Attempt to Validate With Data Unconfounded by Migration and Medical Care.

BACKGROUND: "Scarring in utero" posits that populations exposed to injurious stressors yield birth cohorts that live shorter lives than expected from history. This argument implies a positive historical association between period life expectancy (i.e., average age at death in year t) and cohort life expectancy (i.e., average lifespan of persons born in year t). Tests of the argument have not produced consistent results and appear confounded by autocorrelation, migration, and access to medical care. Here we test whether, as predicted by scarring in utero, sex-specific period and cohort life expectancy appear positively related among Swedes born from 1751 through 1800. If scarring has ever influenced longevity, we should detect signals of its effects in these cohorts because, unlike other populations with known life span, they aged in place and unlikely benefitted from increased access to efficacious medical care. METHODS: We use Box-Jenkins methods to control autocorrelation and measure associations. RESULTS: Contrary to the scarring hypothesis, we find an inverse association between period and cohort life expectancy. Our findings imply that, among males, variation in injurious stress on the population predicted changes in cohort life span ranging from a gain of approximately 67 weeks to a loss of about 45 weeks of life and among females from a gain of approximately 68 weeks to a loss of about 38 weeks of life. CONCLUSION: Epidemiologists trying to understand and explain temporal variation in cohort life expectancy should view the scarring argument with greater skepticism than currently found in the literature.

Changes in Racial and Ethnic Inequities in Pregnancy-Associated Death in the United States During the COVID-19 Pandemic.

Objectives. To examine changes in cause-specific pregnancy-associated deaths during the COVID-19 pandemic by race and ethnicity and assess changes in racial and ethnic inequities in pregnancy-associated deaths. Methods. We used US vital statistics mortality data from 2018 to 2021 to identify pregnancy-associated deaths among females aged 15 to 44 years. We calculated crude pregnancy-associated death rates (deaths per 100 000 live births) by year, cause, and race/ethnicity, percent change in death rate, and the inequity (difference) in rate for each racial or ethnic group compared with non-Hispanic White people. Results. The pregnancy-associated death rate for obstetric, drug-related, homicide, and other causes of death increased during 2020, and obstetric deaths continued to increase in 2021. Overall estimates mask 2021 increases in drug-related deaths among Hispanic, non-Hispanic American Indian and Alaska Native (AI/AN), and non-Hispanic Asian people; increases in homicide among most racial and ethnic groups; and increases in suicide among Hispanic, non-Hispanic AI/AN, and non-Hispanic Asian people. Conclusions. We found disproportionate increases in pregnancy-associated deaths from nonobstetric causes among minoritized racial and ethnic groups during the COVID-19 pandemic. (Am J Public Health. 2024;114(7):733-742. https://doi.org/10.2105/AJPH.2024.307651).

Validation of ICD-10-CM Diagnosis Codes for Gestational Age at Birth.

BACKGROUND: The International Classification of Diseases , 10th Revision, Clinical Modification (ICD-10-CM) introduced diagnosis codes for week of gestation. Our objective was to assess the validity of these codes among live births, which could have major utility in perinatal research and quality improvement. METHODS: We used linked birth certificate and patient discharge data from births in California during 2016-2019 (N = 1,843,992). We identified gestational age using Z3A.xx ICD-10-CM diagnosis codes in birthing patient discharge data and compared it with the gold standard of obstetric estimate, as recorded on the birth certificate. We further assessed sensitivity and specificity of gestational age categories (≥37 weeks, <37 weeks, <32 weeks, <28 weeks), given these categories are frequently of interest, and evaluated differences in validity of preterm birth (<37 weeks' gestation) by patient characteristics. RESULTS: One-million seven-hundred seventy-thousand one-hundred three patients had a gestational age recorded in patient discharge and birth certificate data. When comparing gestational age in patient discharge data with birth certificate data, the concordance correlation coefficient was 0.96 (95% confidence interval [CI] = 0.96, 0.96) and the mean difference between the two measurements was 0.047 weeks (95% CI = 0.046, 0.047 weeks). Ninety-five percent of the differences between the two measurements were between -1.00 week and +1.09 weeks. Sensitivity and specificity were 0.94 to 1.00 for all gestational age categories and were 0.94 to 1.00 for preterm birth across sociodemographic groups. CONCLUSIONS: We found week-specific gestational age at delivery ICD-10-CM diagnosis codes in patient discharge data to have high validity when compared with the best obstetric estimate on the birth certificate.

The Pent-Up Demand for Breastfeeding Among US Women: Trends After COVID-19 Shelter-in-Place.

Objectives. To estimate changes in national breastfeeding trends immediately before and after COVID-19‒related workplace closures in early 2020. Methods. The implementation of shelter-in-place policies in early 2020, when 90% of people in the United States were urged to remain at home, represents a unique natural experiment to assess the pent-up demand for breastfeeding among US women that may be stymied by the lack of a national paid leave policy. We used the 2017-2020 Pregnancy Risk Assessment Monitoring System (n = 118 139) to estimate changes in breastfeeding practices for births occurring before and after shelter-in-place policies were implemented in the United States. We did this in the overall sample and by racial/ethnic and income subgroups. Results. There was no change in breastfeeding initiation and a 17.5% increase in breastfeeding duration after shelter-in-place, with lingering effects through late 2020. High-income and White women demonstrated the largest gains. Conclusions. The United States ranks worse than similar countries when it comes to breastfeeding initiation and duration. This study suggests that this is partly attributable to inadequate access to postpartum paid leave. This study also demonstrates inequities introduced by patterns of remote work during the pandemic. (Am J Public Health. 2023;113(8):870-873. https://doi.org/10.2105/AJPH.2023.307313).

Excess Injury Mortality in Washington State During the 2021 Heat Wave.

PUBLIC HEALTH IMPLICATIONS: Under global warming scenarios, heat waves of this magnitude will become much more common. Adaptation and planning efforts are needed to protect residents of the historically temperate Pacific Northwest for a range of health outcomes. (Am J Public Health. 2023;113(6):657-660. https://doi.org/10.2105/AJPH.2023.307269).

Exposure to the early COVID-19 pandemic and early, moderate and overall preterm births in the United States: A conception cohort approach.

BACKGROUND: The United States (US) data suggest fewer-than-expected preterm births in 2020, but no study has examined the impact of exposure to the early COVID-19 pandemic at different points in gestation on preterm birth. OBJECTIVE: Our objective was to determine-among cohorts exposed to the early COVID-19 pandemic-whether observed counts of overall, early and moderately preterm birth fell outside the expected range. METHODS: We used de-identified, cross-sectional, national birth certificate data from 2014 to 2020. We used month and year of birth and gestational age to estimate month of conception for birth. We calculated the count of overall (<37 weeks gestation), early (<33 weeks gestation) and moderately (33 to <37 weeks gestation) preterm birth by month of conception. We employed time series methods to estimate expected counts of preterm birth for exposed conception cohorts and identified cohorts for whom the observed counts of preterm birth fell outside the 95% detection interval of the expected value. RESULTS: Among the 23,731,146 births in our study, the mean prevalence of preterm birth among monthly conception cohorts was 9.7 per 100 live births. Gestations conceived in July, August or December of 2019-that is exposed to the early COVID-19 pandemic in the first or third trimester-yielded approximately 3245 fewer moderately preterm and 3627 fewer overall preterm births than the expected values for moderate and overall preterm. Gestations conceived in August and October of 2019-that is exposed to the early COVID-19 pandemic in the late second to third trimester-produced approximately 498 fewer early preterm births than the expected count for early preterm. CONCLUSIONS: Exposure to the early COVID-19 pandemic may have promoted longer gestation among close-to-term pregnancies, reduced risk of later preterm delivery among gestations exposed in the first trimester or induced selective loss of gestations.

Characteristics Associated with Reliability in Reporting of Contraceptive Use: Assessing the Reliability of the Contraceptive Calendar in Seven Countries.

Although the reproductive calendar is the primary tool for measuring contraceptive dynamics in low-income settings, the reliability of calendar data has seldom been evaluated, primarily due to the lack of longitudinal panel data. In this research, we evaluated the reproductive calendar using data from the Performance Monitoring for Action Project. We used population-based longitudinal data from nine settings in seven countries: Burkina Faso, Nigeria (Kano and Lagos States), Democratic Republic of Congo (Kinshasa and Kongo Central Provinces), Kenya, Uganda, Cote d'Ivoire, and India. To evaluate reliability, we compared the baseline cross-sectional report of contraceptive use (overall and by contraceptive method), nonuse, or pregnancy with the retrospective reproductive calendar entry for the corresponding month, measured at follow-up. We use multivariable regressions to identify characteristics associated with reliability or reporting. Overall, we find that the reliability of the calendar is in the "moderate/substantial" range for nearly all geographies and tests (Kappa statistics between 0.58 and 0.81). Measures of the complexity of the calendar (number of contraceptive use episodes, using the long-acting method at baseline) are associated with reliability. We also find that women who were using contraception without their partners/husband's knowledge (i.e., covertly) were less likely to report reliably in several countries.

Stop or Switch: Correlates of Stopping Use or Switching Contraceptive Methods While Wanting to Avoid Pregnancy in 48 Low- and Middle-Income Countries.

Contraceptive discontinuation for method-related reasons, while presumably wanting to avoid pregnancy, is a common phenomenon and can contribute to high levels of unmet need and unplanned pregnancies. Some women discontinue contraceptive use and do not quickly resume a method ("stopping"), while others are able to quickly switch to another method to achieve their reproductive goal of avoiding pregnancy ("switching"). We use Demographic and Health Survey data from 48 countries to examine what differentiates women who were able to switch to another method versus those who ultimately stopped entirely, among women who discontinued contraception for method-related reasons. Results show that wanting to limit births, having ever been married, and recent prior use are all associated with switching versus stopping. In addition, we find that women in West and Middle Africa were more likely to stop use compared to women in other regions. Addressing obstacles to contraceptive continuation, including effective method switching, among women who wish to delay or avoid pregnancy should be a priority for global and country initiatives aiming to deliver client-centered care that supports women and couples to make their best family planning choices.

The Relationship Between Contraceptive Method Use and Return of Fecundity Among Women Attempting Pregnancy in Low- and Middle-Income Countries.

One of the most common barriers to using effective family planning methods is the belief that hormonal contraceptives and contraceptive devices have adverse effects on future fertility. Recent evidence from high-income settings suggests that some hormonal contraceptive methods are associated with delays in return of fecundity, yet it is unclear if these findings generalize to low- and middle-income populations, especially in regions where the injectable is widely used and pressure to bear children is significant. Using reproductive calendar data pooled across 47 Demographic and Health Surveys, we find that the unadjusted 12-month probability of pregnancy for women attempting pregnancy after discontinuing traditional methods, condoms, the pill, and the IUD ranged from 86% to 91%. The 12-month probability was lowest among those who discontinued injectables and implants, with approximately 1 out of 5 women not becoming pregnant within one year after discontinuation. Results from multivariable analysis showed that compared with users of either periodic abstinence or withdrawal, users of the pill, IUD, injectable, and implant had lower fecundability following discontinuation, with the largest reductions occurring among women who used injectables and implants. These findings indicate that women's concerns about potential short-term reductions in fecundity following contraceptive use are not unfounded.

Selection in utero against male twins in the United States early in the COVID-19 pandemic.

OBJECTIVES: We aim to contribute to the literature reporting tests of selection in utero. The theory of reproductive suppression predicts that natural selection would conserve mechanisms, referred to collectively as selection in utero, that spontaneously abort fetuses unlikely to thrive as infants in the prevailing environment. Tests of this prediction include reports that women give birth to fewer than expected male twins, historically among the frailest of infants, during stressful times. The onset of the COVID-19 pandemic in the United States in Spring 2020 demonstrably stressed the population. We test the hypothesis that conception cohorts in gestation at the onset of the pandemic in the United States yielded fewer than expected live male twin births. METHODS: We retrieved deidentified data on the universe of live births in the United States from the National Center for Health Statistics birth certificate records. We applied Box-Jenkins time-series methods to the twin secondary sex ratio computed for 77 monthly conception cohorts spanning August 2013 to December 2019 to detect outlying cohorts in gestation at the onset of the pandemic. RESULTS: The twin secondary sex ratio fell below expected values in three conception cohorts (i.e., July, September, and October 2019, all p < .05) exposed in utero to the onset of the pandemic. CONCLUSIONS: Our results add to prior findings consistent with selection in utero. The role of selection in utero in shaping the characteristics of live births cohorts, especially during the COVID-19 pandemic, warrants further scrutiny.

Expectations of non-COVID-19 deaths during the pre-vaccine pandemic: a process-control approach.

BACKGROUND: Debate over "social distancing" as a response to the pandemic includes the claim that disrupting clinical and public health programming dependent on human-to-human contact increased non-COVID-19 deaths. This claim warrants testing because novel pathogens will continue to emerge. Tests, however, appear frustrated by lack of a convention for estimating non-COVID-19 deaths that would have occurred had clinical and public health programming during the pre-vaccine pandemic remained as efficacious as in the pre-pandemic era. Intending to hasten the emergence of such a convention, we describe and demonstrate "new-signal, prior-response expectations" suggested by research and methods at the intersection of epidemiology and process control engineering. METHODS: Using German data, we estimate pre-pandemic public health efficacy by applying Box-Jenkins methods to 271 weekly counts of all-cause deaths from December 29 2014 through March 8 2020. We devise new-signal, prior-response expectations by applying the model to weekly non-COVID-19 deaths from March 9 2020 through December 26 2020. RESULTS: The COVID-19 pandemic did not coincide with more non-COVID-19 deaths than expected from the efficacy of responses to pre-pandemic all-cause deaths. CONCLUSIONS: New-signal, prior-response estimates can contribute to evaluating the efficacy of public health programming in reducing non-COVID-19 deaths during the pre-vaccine pandemic.

Predicting mortality from 57 economic, behavioral, social, and psychological factors.

Behavioral and social scientists have identified many nonbiological predictors of mortality. An important limitation of much of this research, however, is that risk factors are not studied in comparison with one another or from across different fields of research. It therefore remains unclear which factors should be prioritized for interventions and policy to reduce mortality risk. In the current investigation, we compare 57 factors within a multidisciplinary framework. These include (i) adverse socioeconomic and psychosocial experiences during childhood and (ii) socioeconomic conditions, (iii) health behaviors, (iv) social connections, (v) psychological characteristics, and (vi) adverse experiences during adulthood. The current prospective cohort investigation with 13,611 adults from 52 to 104 y of age (mean age 69.3 y) from the nationally representative Health and Retirement Study used weighted traditional (i.e., multivariate Cox regressions) and machine-learning (i.e., lasso, random forest analysis) statistical approaches to identify the leading predictors of mortality over 6 y of follow-up time. We demonstrate that, in addition to the well-established behavioral risk factors of smoking, alcohol abuse, and lack of physical activity, economic (e.g., recent financial difficulties, unemployment history), social (e.g., childhood adversity, divorce history), and psychological (e.g., negative affectivity) factors were also among the strongest predictors of mortality among older American adults. The strength of these predictors should be used to guide future transdisciplinary investigations and intervention studies across the fields of epidemiology, psychology, sociology, economics, and medicine to understand how changes in these factors alter individual mortality risk.

Patterned Outcomes, Unpatterned Counterfactuals, and Spurious Results: Perinatal Health Outcomes Following COVID-19.

The epidemiologic literature estimating the indirect or secondary effects of the coronavirus disease 2019 (COVID-19) pandemic on pregnant people and gestation continues to grow. Our assessment of this scholarship, however, leads us to suspect that the methods most commonly used may lead researchers to spurious inferences. This suspicion arises because the methods do not account for temporal patterning in perinatal outcomes when deriving counterfactuals, or estimates of the outcomes had the pandemic not occurred. We illustrate the problem in 2 ways. First, using monthly data from US birth certificates, we describe temporal patterning in 5 commonly used perinatal outcomes. Notably, for all but 1 outcome, temporal patterns appear more complex than much of the emerging literature assumes. Second, using data from France, we show that using counterfactuals that ignore this complexity produces spurious results. We recommend that subsequent investigations on COVID-19 and other perturbations use widely available time-series methods to derive counterfactuals that account for strong temporal patterning in perinatal outcomes.

The 2016 Presidential Election and Prenatal Care Utilization Among Foreign-born Hispanic Pregnant People.

BACKGROUND: Few studies have evaluated the relationship between adequate and timely prenatal care among immigrant pregnant people and the recent political climate, including the 2016 election and associated campaigns. OBJECTIVES: We examine whether the 2016 presidential election was associated with changes in prenatal care utilization among US foreign-born Hispanic pregnant people. RESEARCH DESIGN: Interrupted time series. SUBJECTS: All foreign-born Hispanic and US-born non-Hispanic White people delivering singleton infants from 2008 to 2017 who resided in the 23 states that fully implemented the 2003 version of the birth certificate before January 2008 (n=12,397,503). MEASURES: We examine the relationship between the presidential election and changes in the odds of inadequate or late/no prenatal care among immigrant Hispanic pregnant people, as well as trends in prenatal care utilization before the election. RESULTS: Our results show no unexpected changes in receipt of inadequate prenatal care, and late/no prenatal care, among the 7 monthly conception cohorts exposed to the election before the third trimester. However, we detected increases in the odds of both inadequate care and late/no prenatal care among foreign-born Hispanic pregnant people in June 2015 and January 2016, respectively. These upward level shifts persisted through the remainder of our time series ending with the cohort conceived around December 2016. CONCLUSIONS: The worsening shifts in prenatal care utilization we observe may serve as a bellwether for worsening outcomes among immigrant women and their families. Research is therefore urgently needed to investigate the determinants and consequences of these concerning trends.

Estimating misclassification errors in the reporting of maternal mortality in national civil registration vital statistics systems: A Bayesian hierarchical bivariate random walk model to estimate sensitivity and specificity for multiple countries and years with missing data.

Civil registration vital statistics (CRVS) systems provide data on maternal mortality that can be used for monitoring trends and to inform policies and programs. However, CRVS maternal mortality data may be subject to substantial reporting errors due to misclassification of maternal deaths. Information on misclassification is available for selected countries and periods only. We developed a Bayesian hierarchical bivariate random walk model to estimate sensitivity and specificity for multiple populations and years and used the model to estimate misclassification errors in the reporting of maternal mortality in CRVS systems. The proposed Bayesian misclassification (BMis) model captures differences in sensitivity and specificity across populations and over time, allows for extrapolations to periods with missing data, and includes an exact likelihood function for data provided in aggregated form. Validation exercises using maternal mortality data suggest that BMis is reasonably well calibrated and improves upon the CRVS-adjustment approach used until 2018 by the UN Maternal Mortality Inter-Agency Group (UN-MMEIG) to account for bias in CRVS data resulting from misclassification error. Since 2019, BMis is used by the UN-MMEIG to account for misclassification errors when estimating maternal mortality using CRVS data.

Changes in preterm birth and caesarean deliveries in the United States during the SARS-CoV-2 pandemic.

BACKGROUND: Preliminary studies suggest that the SARS-CoV-2 pandemic and associated social, economic and clinical disruptions have affected pregnancy decision-making and outcomes. Whilst a few US-based studies have examined regional changes in birth outcomes during the pandemic's first months, much remains unknown of how the pandemic impacted perinatal health indicators at the national-level throughout 2020, including during the 'second wave' of infections that occurred later in the year. OBJECTIVES: To describe changes in monthly rates of perinatal health indicators during the 2020 pandemic for the entire US. METHODS: For the years 2015 to 2020, we obtained national monthly rates (per 100 births) for four perinatal indicators: preterm (<37 weeks' gestation), early preterm (<34 weeks' gestation), late preterm (34-36 weeks' gestation) and caesarean delivery. We used an interrupted time-series approach to compare the outcomes observed after the pandemic began (March 2020) to those expected had the pandemic not occurred for March through December of 2020. RESULTS: Observed rates of preterm birth fell below expectation across several months of the 2020 pandemic. These declines were largest in magnitude in early and late 2020, with a 5%-6% relative difference between observed and expected occurring in March and November. For example, in March 2020, the observed preterm birth rate of 9.8 per 100 live births fell below the 95% prediction interval (PI) of the rate predicted from history, which was 10.5 preterm births per 100 live births (95% PI 10.2, 10.7). We detected no changes from expectation in the rate of caesarean deliveries. CONCLUSIONS: Our findings provide nationwide evidence of unexpected reductions in preterm delivery during the 2020 SARS-CoV-2 pandemic in the US. Observed declines below expectation were differed by both timing of delivery and birth month, suggesting that several mechanisms, which require further study, may explain these patterns.

Perceptions of Partners' Fertility Preferences and Women's Covert Contraceptive Use in Eight Sub-Saharan African Countries.

Covert use of contraception is a common but underreported and understudied phenomenon where one partner uses contraception without the other's knowledge. We used Demographic and Health Survey couple data to examine the relationship between wives' perceptions of husbands' fertility preferences and type of contraceptive use (overt vs. covert) in Benin, Ethiopia, Kenya, Mali, Nigeria, Sierra Leone, Uganda, and Zambia using logistic regression. Wives who perceived that their husbands wanted more children than them had increased odds of using covertly, compared to those who perceived that husbands wanted the same number of children in all countries except Benin, and the strength of the relationships ranged from adjusted odds ratio (aOR) 2.89 (95 percent confidence interval (CI) 1.75-4.76) in Zambia to aOR 4.01 (95 percent CI 1.68-9.58) in Mali. Wives who reported not knowing their husbands' fertility preferences had increased odds of using covertly compared to wives who perceived that their husbands wanted the same number of children in all countries except Zambia, ranging from aOR 2.02 (95 percent CI 1.11-3.69) in Ethiopia to aOR 3.82 (95 percent CI 2.29-6.37) in Kenya. Our findings indicate that efforts to increase partner engagement to align couple's fertility preferences may encourage overt use.

Stressful life events and prescription opioid use during pregnancy: findings from the 2019 pregnancy risk assessment monitoring system.

OBJECTIVE: Prescription opioid use during pregnancy poses risk to maternal and infant health. However, there is limited research on proximate risk factors for prescription opioid use during pregnancy. This study aimed to evaluate the relationship between stressful life events experienced in the 12 months prior to birth and prescription opioid use during pregnancy. METHODS: Data from the 2019 Pregnancy Risk Assessment Monitoring System were analyzed (N = 17,812 women who delivered a live birth in 2019). Logistic regression and multinomial logistic regression analyses were used to assess the association between levels of stressful life events (0, 1-2, 3-5, or 6+) on (1) prescription opioid use, (2) combined opioid use (mono- or poly-opioid use), and (3) patterns of opioid use (pain management, opioid misuse) during pregnancy while controlling for socio-demographic characteristics, patterns of substance use prior to pregnancy, and pregnancy-related characteristics. RESULTS: Women with a greater accumulation of stressful life events in the 12 months prior to birth-especially 6 or more-had increased likelihood of prescription opioid use. Accumulating stressful life events were also associated with a higher risk of poly-opioid use, as well as using prescription opioids for pain management and patterns of opioid misuse. CONCLUSION: Stressful life events are a risk factor for prescription opioid use during pregnancy. Considering the harms posed by both stressors and opioid use for maternal and infant wellbeing, future research should assess efforts to prevent and manage stressful life events to reduce opioid use during pregnancy.

Demographic and Fertility Characteristics of Contraceptive Clusters in Burundi.

Examining women's reproductive experiences over time reveals a more dynamic view of women's behaviors and needs than current status measures alone. This study uses sequence and cluster analyses, which are designed for identifying patterns and subgroups in longitudinal data. We apply these methods to contraceptive calendar data in Burundi to identify discrete clusters of women based on contraceptive and pregnancy behaviors over the past 5 years. We identify six unique clusters; three characterized by no use of contraception (85 percent of women) and three by use (16 percent). The Quiet Calendar cluster (42 percent) comprise women who neither experience pregnancy nor use contraception. Family Builder 1 (25 percent) and 2 (18 percent) both include women who experience two pregnancies, but differ in unmet need and lifetime experience with contraception. Modern Mother (8 percent), Consistently Covered Mother (6 percent), and Traditional Mother (2 percent) clusters differ by type of contraception used following pregnancy. Factors associated with cluster membership are need for family planning, lifetime experience with contraception, marital status, pregnancy intention, and age. This clustering approach provides a new, more holistic way to measure the diverse needs across unique subpopulations and can inform the development of multifaceted, adaptable strategies to meet women's dynamic fertility needs over the reproductive life course.