Biostatistics and Epidemiology Faculty Publications Series

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  • Publication
    Vitamin D Status Is Not Associated with Risk of Early Menopause
    (2018-01-01) Purdue-Smith, Alexandra C.; Whitcomb, Brian W.; Manson, JoAnn E.; Hankinson, Susan E.; Troy, Lisa M.; Rosner, Bernard A.; Bertone-Johnson, Elizabeth R.
    Background: Early natural menopause, the cessation of ovarian function before age 45 y, is positively associated with cardiovascular disease and other conditions. Dietary vitamin D intake has been inversely associated with early menopause; however, no previous studies have evaluated risk with regard to plasma 25-hydroxyvitamin D [25(OH)D] concentrations. Objective: We prospectively evaluated associations of total and free 25(OH)D and vitamin D–binding protein (VDBP) concentrations and the risk of early menopause in a case-control study nested within the Nurses’ Health Study II (NHS2). We also considered associations of 25(OH)D and VDBP with anti-Müllerian hormone (AMH) concentrations. Methods: The NHS2 is a prospective study in 116,430 nurses, aged 25–42 y at baseline (1989). Premenopausal plasma blood samples were collected between 1996 and 1999, from which total 25(OH)D and VDBP concentrations were measured and free 25(OH)D concentrations were calculated. Cases experienced menopause between blood collection and age 45 y (n = 328) and were matched 1:1 by age and other factors to controls who experienced menopause after age 48 y (n = 328). Conditional logistic regression models were used to estimate ORs and 95% CIs for early menopause according to each biomarker. Generalized linear models were used to estimate AMH geometric means according to each biomarker. Results: After adjusting for smoking and other factors, total and free 25(OH)D were not associated with early menopause. Quartile 4 compared with quartile 1 ORs were 1.04 (95% CI: 0.60, 1.81) for total 25(OH)D and 0.70 (95% CI: 0.41, 1.20) for free 25(OH)D. 25(OH)D was unrelated to AMH concentrations. VDBP was positively associated with early menopause; the OR comparing the highest with the lowest quartile of VDBP was 1.80 (95% CI: 1.09, 2.98). Conclusions: Our findings suggest that total and free 25(OH)D are not importantly related to the risk of early menopause. VDBP may be associated with increased risk, but replication is warranted.
  • Publication
    Global, regional, and national mortality trends in older children and young adolescents (5–14 years) from 1990 to 2016: an analysis of empirical data
    (2018-01-01) Masquelier, Bruno; Hug, Lucia; Sharrow, David; You, Danzhen; Hogan, Daniel; Hill, Kenneth; Liu, Jing; Pedersen, Jon; Alkema, Leontine
    Summary Background From 1990 to 2016, the mortality of children younger than 5 years decreased by more than half, and there are plentiful data regarding mortality in this age group through which we can track global progress in reducing the under-5 mortality rate. By contrast, little is known on how the mortality risk among older children (5–9 years) and young adolescents (10–14 years) has changed in this time. We aimed to estimate levels and trends in mortality of children aged 5–14 years in 195 countries from 1990 to 2016. Methods In this analysis of empirical data, we expanded the United Nations Inter-agency Group for Child Mortality Estimation database containing data on children younger than 5 years with 5530 data points regarding children aged 5–14 years. Mortality rates from 1990 to 2016 were obtained from nationally representative birth histories, data on household deaths reported in population censuses, and nationwide systems of civil registration and vital statistics. These data were used in a Bayesian B-spline bias-reduction model to generate smoothed trends with 90% uncertainty intervals, to determine the probability of a child aged 5 years dying before reaching age 15 years. Findings Globally, the probability of a child dying between the ages 5 years and 15 years was 7·5 deaths (90% uncertainty interval 7·2–8·3) per 1000 children in 2016, which was less than a fifth of the risk of dying between birth and age 5 years, which was 41 deaths (39–44) per 1000 children. The mortality risk in children aged 5–14 years decreased by 51% (46–54) between 1990 and 2016, despite not being specifically targeted by health interventions. The annual number of deaths in this age group decreased from 1·7 million (1·7 million–1·8 million) to 1 million (0·9 million–1·1 million) in 1990–2016. In 1990–2000, mortality rates in children aged 5–14 years decreased faster than among children aged 0–4 years. However, since 2000, mortality rates in children younger than 5 years have decreased faster than mortality rates in children aged 5–14 years. The annual rate of reduction in mortality among children younger than 5 years has been 4·0% (3·6–4·3) since 2000, versus 2·7% (2·3–3·0) in children aged 5–14 years. Older children and young adolescents in sub-Saharan Africa are disproportionately more likely to die than those in other regions; 55% (51–58) of deaths of children of this age occur in sub-Saharan Africa, despite having only 21% of the global population of children aged 5–14 years. In 2016, 98% (98–99) of all deaths of children aged 5–14 years occurred in low-income and middle-income countries, and seven countries alone accounted for more than half of the total number of deaths of these children. Interpretation Increased efforts are required to accelerate reductions in mortality among older children and to ensure that they benefit from health policies and interventions as much as younger children. Funding UN Children's Fund, Bill & Melinda Gates Foundation, United States Agency for International Development.
  • Publication
    The Effect of Cluster Size Variability on Statistical Power in Cluster-Randomized Trials
    (2015-01-01) Lauer, Stephen A.; Kleinman, Ken P.; Reich, Nicholas G.
    The frequency of cluster-randomized trials (CRTs) in peer-reviewed literature has increased exponentially over the past two decades. CRTs are a valuable tool for studying interventions that cannot be effectively implemented or randomized at the individual level. However, some aspects of the design and analysis of data from CRTs are more complex than those for individually randomized controlled trials. One of the key components to designing a successful CRT is calculating the proper sample size (i.e. number of clusters) needed to attain an acceptable level of statistical power. In order to do this, a researcher must make assumptions about the value of several variables, including a fixed mean cluster size. In practice, cluster size can often vary dramatically. Few studies account for the effect of cluster size variation when assessing the statistical power for a given trial. We conducted a simulation study to investigate how the statistical power of CRTs changes with variable cluster sizes. In general, we observed that increases in cluster size variability lead to a decrease in power.
  • Publication
    The importance of friends and family to recreational gambling, at-risk gambling, and problem gambling
    (2018-01-01) Mazar, Alissa; Williams, Robert J.; Stanek, Edward J.; Zorn, Martha; Volberg, Rachel A.
    Background The variables correlated with problem gambling are routinely assessed and fairly well established. However, problem gamblers were all ‘at-risk’ and ‘recreational’ gamblers at some point. Thus, it is instructive from a prevention perspective to also understand the variables which discriminate between recreational gambling and at-risk gambling and whether they are similar or different to the ones correlated with problem gambling. This is the purpose of the present study. Method Between September 2013 to May 2014, a representative sample of 9,523 Massachusetts adults was administered a comprehensive survey of their past year gambling behavior and problem gambling symptomatology. Based on responses to the Problem and Pathological Gambling Measure, respondents were categorized as Non-Gamblers (2,523), Recreational Gamblers (6,271), At-Risk Gamblers (600), or Problem/Pathological Gamblers (129). With the reference category of Recreational Gambler, a series of binary logistic regressions were conducted to identify the demographic, health, and gambling related variables that differentiated Recreational Gamblers from Non-Gamblers, At-Risk-Gamblers, and Problem/Pathological Gamblers. Results The strongest discriminator of being a Non-Gambler rather than a Recreational Gambler was having a lower portion of friends and family that were regular gamblers. Compared to Recreational Gamblers, At-Risk Gamblers were more likely to: gamble at casinos; play the instant and daily lottery; be male; gamble online; and be born outside the United States. Compared to Recreational Gamblers, Problem and Pathological Gamblers were more likely to: play the daily lottery; be Black; gamble at casinos; be male; gamble online; and play the instant lottery. Importantly, having a greater portion of friends and family who were regular gamblers was the second strongest correlate of being both an At-Risk Gambler and Problem/Pathological Gambler. Conclusions These analyses offer an examination of the similarities and differences between gambling subtypes. An important finding throughout the analyses is that the gambling involvement of family and friends is strongly related to Recreational Gambling, At-Risk Gambling, and Problem/Pathological Gambling. This suggests that targeting the social networks of heavily involved Recreational Gamblers and At-Risk Gamblers (in addition to Problem/Pathological Gamblers) could be an important focus of efforts in problem gambling prevention.
  • Publication
    Comparison of combination methods to create calibrated ensemble forecasts for seasonal influenza in the U.S.
    (2023-01-01) Wattanachit, Nutcha; Ray, Evan L.; McAndrew, Thomas C.; Reich, Nicholas G.
    The characteristics of influenza seasons vary substantially from year to year, posing challenges for public health preparation and response. Influenza forecasting is used to inform seasonal outbreak response, which can in turn potentially reduce the impact of an epidemic. The United States Centers for Disease Control and Prevention, in collaboration with external researchers, has run an annual prospective influenza forecasting exercise, known as the FluSight challenge. Uniting theoretical results from the forecasting literature with domain-specific forecasts from influenza outbreaks, we applied parametric forecast combination methods that simultaneously optimize model weights and calibrate the ensemble via a beta transformation and made adjustments to the methods to reduce their complexity. We used the beta-transformed linear pool, the finite beta mixture model, and their equal weight adaptations to produce ensemble forecasts retrospectively for the 2016/2017, 2017/2018, and 2018/2019 influenza seasons in the U.S. We compared their performance to methods that were used in the FluSight challenge to produce the FluSight Network ensemble, namely the equally weighted linear pool and the linear pool. Ensemble forecasts produced from methods with a beta transformation were shown to outperform those from the equally weighted linear pool and the linear pool for all week-ahead targets across in the test seasons based on average log scores. We observed improvements in overall accuracy despite the beta-transformed linear pool or beta mixture methods' modest under-prediction across all targets and seasons. Combination techniques that explicitly adjust for known calibration issues in linear pooling should be considered to improve probabilistic scores in outbreak settings.