A longitudinal investigation of breastfeeding planning, initiation, and duration among individuals with pre-pregnancy overweight or obesity.

Individuals with a body mass index (BMI)≥25 kg/m2 are less likely to initiate and continue breastfeeding than are those with BMIs<25. Given the intergenerational health benefits of breastfeeding, it is important to understand breastfeeding behaviors and their correlates among individuals with BMIs≥25. Thus, in an observational cohort with BMI≥25 (N = 237), we aimed to characterize longitudinal relationships among breastfeeding planning, initiation, and duration and their sociodemographic/clinical correlates and determine if pre-pregnancy BMI predicts breastfeeding planning, initiation, and duration. Breastfeeding behaviors, weight/BMI, and sociodemographic/clinical characteristics were assessed in early, mid, and late pregnancy, and at six-months postpartum. Most participants planned to (84%) and initiated (81%) breastfeeding, of which 37% breastfed for ≥6 months. Participants who were married, first-time parents, higher in education/income, and had never smoked tobacco were more likely to plan, initiate, and achieve ≥6 months of breastfeeding. Higher pre-pregnancy BMI was not associated with breastfeeding planning or initiation but was associated with lower adjusted odds of breastfeeding for ≥6 months relative to <6 months. Findings suggest that support aimed at extending breastfeeding among those with elevated pre-pregnancy BMI may be warranted. Future interventions should also address sociodemographic and clinical inequities in breastfeeding.

The association between multidimensional sleep health and gestational weight gain.

BACKGROUND: Although poor sleep health is associated with weight gain and obesity in the non-pregnant population, research on the impact of sleep health on weight change among pregnant people using a multidimensional sleep health framework is needed. OBJECTIVES: This secondary data analysis of the Nulliparous Pregnancy Outcome Study: Monitoring Mothers-to-be Sleep Duration and Continuity Study (n = 745) examined associations between mid-pregnancy sleep health indicators, multidimensional sleep health and gestational weight gain (GWG). METHODS: Sleep domains (i.e. regularity, nap duration, timing, efficiency and duration) were assessed via actigraphy between 16 and 21 weeks of gestation. We defined 'healthy' sleep in each domain with empirical thresholds. Multidimensional sleep health was based on sleep profiles derived from latent class analysis and composite score defined as the sum of healthy sleep domains. Total GWG, the difference between self-reported pre-pregnancy weight and the last measured weight before delivery, was converted to z-scores using gestational age- and BMI-specific charts. GWG was defined as low (<-1 SD), moderate (-1 or +1 SD) and high (>+1 SD). RESULTS: Nearly 50% of the participants had a healthy sleep profile (i.e. healthy sleep in most domains), whereas others had a sleep profile defined as having varying degrees of unhealthy sleep in each domain. The individual sleep domains were associated with a 20%-30% lower risk of low or high GWG. Each additional healthy sleep indicator was associated with a 10% lower risk of low (vs. moderate), but not high, GWG. Participants with late timing, long duration and low efficiency (vs. healthy) profiles had the strongest risk of low GWG (relative risk 1.5, 95% confidence interval 0.9, 2.4). Probabilistic bias analysis suggested that most associations between individual sleep health indicators, sleep health profiles and GWG were biased towards the null. CONCLUSIONS: Future research should determine whether sleep health is an intervention target for healthy GWG.

Inter-rater reliability of the infectious disease modeling reproducibility checklist (IDMRC) as applied to COVID-19 computational modeling research.

BACKGROUND: Infectious disease computational modeling studies have been widely published during the coronavirus disease 2019 (COVID-19) pandemic, yet they have limited reproducibility. Developed through an iterative testing process with multiple reviewers, the Infectious Disease Modeling Reproducibility Checklist (IDMRC) enumerates the minimal elements necessary to support reproducible infectious disease computational modeling publications. The primary objective of this study was to assess the reliability of the IDMRC and to identify which reproducibility elements were unreported in a sample of COVID-19 computational modeling publications. METHODS: Four reviewers used the IDMRC to assess 46 preprint and peer reviewed COVID-19 modeling studies published between March 13th, 2020, and July 30th, 2020. The inter-rater reliability was evaluated by mean percent agreement and Fleiss' kappa coefficients (κ). Papers were ranked based on the average number of reported reproducibility elements, and average proportion of papers that reported each checklist item were tabulated. RESULTS: Questions related to the computational environment (mean κ = 0.90, range = 0.90-0.90), analytical software (mean κ = 0.74, range = 0.68-0.82), model description (mean κ = 0.71, range = 0.58-0.84), model implementation (mean κ = 0.68, range = 0.39-0.86), and experimental protocol (mean κ = 0.63, range = 0.58-0.69) had moderate or greater (κ > 0.41) inter-rater reliability. Questions related to data had the lowest values (mean κ = 0.37, range = 0.23-0.59). Reviewers ranked similar papers in the upper and lower quartiles based on the proportion of reproducibility elements each paper reported. While over 70% of the publications provided data used in their models, less than 30% provided the model implementation. CONCLUSIONS: The IDMRC is the first comprehensive, quality-assessed tool for guiding researchers in reporting reproducible infectious disease computational modeling studies. The inter-rater reliability assessment found that most scores were characterized by moderate or greater agreement. These results suggest that the IDMRC might be used to provide reliable assessments of the potential for reproducibility of published infectious disease modeling publications. Results of this evaluation identified opportunities for improvement to the model implementation and data questions that can further improve the reliability of the checklist.

Sleep characteristics modify the associations of physical activity during pregnancy and gestational weight gain.

OBJECTIVE: Excessive gestational weight gain (eGWG) is associated with adverse long-term maternal outcomes. Most lifestyle interventions that incorporate physical activity have been ineffective at reducing eGWG. The purpose of this study was to determine if sleep modified the relationships between physical activity change from the 2nd to 3rd trimester and the odds of excessive gestational weight gain (eGWG). METHODS: This was a secondary data analysis of a prospective cohort study of pregnant birthing people with overweight or obesity (n = 105). We estimated physical activity energy expenditure (PAEE) in the 2nd and 3rd trimesters of pregnancy and sleep characteristics (i.e., sleep quality, daytime dysfunction, sleep efficiency, sleep duration) in the 2nd trimester of pregnancy with validated measures. We used regression models with sleep and PAEE change (increase/stable vs. decrease) interaction terms to examine the impact of sleep on PAEE change and eGWG. RESULTS: Mean GWG was 37.02 ± 16.76 lbs. and 80% of participants experienced eGWG. Eighteen percent of participants increased their PAEE from the 2nd to the 3rd trimester. Increasing (vs. decreasing) PAEE was associated with lower log-odds of eGWG only among participants that slept at least 8 h/night (p = 0.06), had at least 85% sleep efficiency (p = 0.03), or reported less daytime dysfunction (p = 0.08). Sleep quality did not moderate the association between PAEE change and eGWG. CONCLUSIONS: Weight management interventions in pregnancy should consider screening for and addressing poor sleep in the second trimester.

The Impact of a Randomized Controlled Trial of a Lifestyle Intervention on Sleep Among Latina Postpartum Women.

BACKGROUND: Poor sleep is associated with adverse outcomes among postpartum women. Exercise may improve sleep, but this has not been well examined in the postpartum period. PURPOSE: To examine the impact of a culturally modified, individually tailored lifestyle intervention on sleep outcomes among postpartum Latina women. METHODS: Estudio PARTO was a randomized controlled trial aimed at reducing Type 2 diabetes among Latina women with abnormal glucose tolerance in pregnancy. Participants were randomized to a lifestyle (i.e., diet and exercise; n = 70) or a health and wellness control intervention (n = 78) in late pregnancy (baseline). The Pittsburgh Sleep Quality Index (PSQI) was used to measure sleep quality (PSQI score), onset latency (minutes per night), duration (hours per night), efficiency (percentage of the time in bed asleep), and daytime dysfunction at baseline, 6 weeks, 6 months, and 12 months postpartum. RESULTS: Mean PSQI score (6.56 ± 3.87), sleep duration (6.84 ± 1.75 hr/night), and sleep efficiency (79.70% ± 18.10%) did not differ between the arms at baseline. Mixed-effects models indicated a greater decrease of 1.29 in PSQI score (i.e., improved sleep quality) in the lifestyle versus health and wellness arm (95% confidence interval [CI] = -2.50 to -0.08, p = .04) over follow-up. There was the suggestion of a smaller decrease in sleep duration (mean = 0.48 hr/night, 95% CI = -0.10 to 1.06, p = .10) in the lifestyle versus health and wellness arm. There were no statistically significant differences in other sleep outcomes between arms. CONCLUSIONS: Findings suggest that lifestyle interventions improve sleep quality but not sleep duration, sleep onset latency, sleep efficiency, or daytime dysfunction in postpartum Latina women and, therefore, may hold promise for improving subsequent mental and physical health in this population. CLINICAL TRIALS REGISTRATION: NCT01679210.

The Preliminary Efficacy of a Sleep Self-management Intervention Using a Personalized Health Monitoring Device during Pregnancy.

Background: Sleep disturbances are common during pregnancy and are associated with the development of adverse pregnancy outcomes. Personal health monitors (PHM) can facilitate change in health behaviors, though few studies have examined their use in improving sleep during pregnancy. This pilot study aimed to characterize sleep changes during pregnancy in women participating in a self-management intervention using a PHM.Participants/Methods: Participants with low risk, singleton pregnancies from Western Massachusetts were randomized at 24 weeks gestation to receive sleep education only (n = 12) or sleep education, and PHM intervention (n = 12). The single-session sleep education was given at baseline by a registered nurse. Sleep quality, duration, efficiency, disturbances, daytime sleepiness, and fatigue were assessed at baseline and 12 weeks follow-up using questionnaires. We described mean ± standard deviation within and between-group changes in each sleep outcome from baseline to 12 weeks follow-up.Results: The PHM arm experienced larger sleep quality improvements and daytime sleepiness than the sleep-education only arm, but the differences were not statistically significant. In the PHM arm, the Pittsburgh Sleep Quality Index (PSQI) score decreased (i.e., sleep quality increased) 1.22 ± 2.39 (p = .16), and the Epworth Sleepiness Scale (ESS) score decreased (i.e., daytime sleepiness decreased) 1.11 ± 2.08 (p = .15). In the sleep-education arm PSQI decreased 0.57 ± 2.37 (p = .55) and ESS decreased 1.29 ± 2.93 (p = .29). Neither group experienced statistically significant changes in sleep duration, efficiency, disturbances, or fatigue.Conclusion: Sleep education with PHM may improve or prevent decreases in sleep outcomes during pregnancy. Further investigation in larger trials is warranted.

Feasibility of a pilot, randomized controlled trial using a personalized health monitoring device with pregnant women for behavioral sleep research.

Sleep disruptions are common in pregnancy and can have significant maternal and infant health consequences. Management of sleep using a personal health monitoring (PHM) device may be effective in promoting behavior change and contribute to improved pregnancy-related sleep. The purpose of this pilot, randomized controlled trial was to determine the feasibility of recruitment (i.e., recruiting a 20% minority sample, most successful recruitment methods), retention, adherence, and data collection methods with a sample of pregnant women (n = 24) at 24 weeks gestation for a 12-week intervention using a PHM device. Of 24 enrolled participants, 20 (83%) were retained through the 12-week intervention and the follow-up at 2-4 weeks postpartum. The majority of participants had a four-year education and identified as White. Ninety-one percent (n = 11) wore the device for at least ten weeks. Pregnant women may be willing engage in sleep intervention research and wear a PHM to self-monitor sleep during pregnancy. Future research should consider recruitment methods tailored to recruit diverse populations of pregnant women.

Physical Activity and Sleep Quality and Duration During Pregnancy Among Hispanic Women: Estudio PARTO.

Objective/Background: Poor sleep during pregnancy is common and is associated with pregnancy complications. Physical activity (PA) is associated with better sleep in nonpregnant populations. However, studies among pregnant women are sparse, conflicting, and none have been conducted among Hispanic women, who face a disproportionate burden of poor sleep and pregnancy complications. Therefore, our objective was to examine the relationship between intensity- and domain-specific PA, respectively, on sleep quality and duration among Hispanic pregnant women. Participants: We evaluated these associations among participants (n = 251) in Estudio PARTO, an ongoing randomized controlled trial aimed at reducing type 2 diabetes among women at high risk. Methods: We assessed the cross-sectional relationship between PA (via Pregnancy PA Questionnaire) and sleep quality and duration (via Pittsburgh Sleep Quality Index) using baseline data (26.5 ± 6.9 weeks gestation). Results: In multivariable logistic models, household and caregiving activities were associated with higher odds of very poor sleep quality (OR = 2.69; 95% CI = 1.04 to 7.04) and with short (vs. medium) sleep duration (OR = 2.85; 95% CI = 1.07 to 7.56). In contrast, occupational PA was associated with lower odds of very poor sleep quality (OR = 0.39; 95% CI = 0.17 to 0.89). Light-intensity PA was associated with lower odds of long (vs. medium) sleep duration (OR = 0.13; 95% CI = 0.03 to 0.52). There were no statistically significant relationships between PA in any other domain and sleep. Conclusions: Prospective studies will be critical in evaluating the potential adverse impact of household and caregiving activities on poor sleep quality.

A prospective study of physical activity and fecundability in women with a history of pregnancy loss.

STUDY QUESTION: Is physical activity (PA) associated with fecundability in women with a history of prior pregnancy loss? SUMMARY ANSWER: Higher fecundability was related to walking among overweight/obese women and to vigorous PA in women overall. WHAT IS KNOWN ALREADY: PA may influence fecundability through altered endocrine function. Studies evaluating this association have primarily utilized Internet-based recruitment and self-report for pregnancy assessment and have yielded conflicting results. STUDY DESIGN, SIZE, DURATION: This is a secondary analysis of the Effects of Aspirin in Gestation and Reproduction (EAGeR) trial (2007-2011), a multisite, randomized controlled trial of preconception-initiated low-dose aspirin. PARTICIPANTS/MATERIALS, SETTING, METHODS: Healthy women (n = 1214), aged 18-40 and with 1-2 prior pregnancy losses, were recruited from four US medical centers. Participants were followed for up to six menstrual cycles while attempting pregnancy and through pregnancy for those who became pregnant. Time to hCG detected pregnancy was assessed using discrete-time Cox proportional hazard models to estimate fecundability odds ratios (FOR) adjusted for covariates, accounting for left truncation and right censoring. MAIN RESULTS AND THE ROLE OF CHANCE: The association of walking with fecundability varied significantly by BMI (P-interaction = 0.01). Among overweight/obese women, walking ≥10 min at a time was related to improved fecundability (FOR = 1.82, 95% CI: 1.19, 2.77). In adjusted models, women reporting >4 h/wk of vigorous activity had significantly higher fecundability (FOR = 1.69, 95% CI: 1.24, 2.31) compared to no vigorous activity. Associations of vigorous activity with fecundability were not significantly different by BMI (P-interaction = 0.9). Moderate activity, sitting, and International Physical Activity Questionnaire (IPAQ) categories were not associated with fecundability overall or in BMI-stratified analyses. LIMITATIONS, REASONS FOR CAUTION: Some misclassification of PA levels as determined by the short form of the IPAQ is likely to have occurred, and may have led to non-differential misclassification of exposure in our study. Information on diet and change in BMI was not collected and may have contributed to some residual confounding in our results. The generalizability of our results may be limited as our population consisted of women with a history of one or two pregnancy losses. WIDER IMPLICATIONS OF THE FINDINGS: These findings provide positive evidence for the benefits of PA in women attempting pregnancy, especially for walking among those with higher BMI. Further study is necessary to clarify possible mechanisms through which walking and vigorous activity might affect time-to-pregnancy. STUDY FUNDING/COMPETING INTEREST(S): This work was funded by the Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development. The authors report no conflicts of interest in this work. TRIAL REGISTRATION NUMBER: #NCT00467363.

The impact of an exercise intervention on C - reactive protein during pregnancy: a randomized controlled trial.

BACKGROUND: C-reactive protein (CRP) during pregnancy has been associated with adverse maternal outcomes such as preeclampsia and gestational diabetes mellitus. Randomized trials suggest that exercise programs may be associated with reductions in CRP in non-pregnant populations; however, such studies have not been conducted among pregnant women. The purpose of this study was to evaluate the impact of an individually-tailored motivationally-matched exercise intervention on CRP in pregnant women. METHODS: The Behaviors Affecting Baby and You study was a randomized controlled trial of prenatal physical activity to prevent the development of gestational diabetes mellitus in women at increased risk. Women were randomized to either a 12-week exercise intervention (n = 84) or a comparison health and wellness intervention (n = 87). High sensitivity CRP (mg/dL) was measured using a commercial immunoassay kit. Physical activity was measured using the Pregnancy Physical Activity Questionnaire. Mixed model analyses were used to evaluate the impact of the intervention on change in CRP using an intent-to-treat approach. RESULTS: CRP decreased (-0.09 mg/dL, 95 % CI: -0.25, 0.07) from pre- to post-intervention in the exercise arm (p = 0.14) and increased (0.08 mg/dL, 95 % CI: -0.07, 0.24) (p = 0.64) in the health and wellness arm; however the between group difference was not statistically significant (p = 0.14). Findings did not differ according to ethnic group or pre-pregnancy body mass index. In a secondary analysis based on self-reported physical activity, women who decreased their time spent in sports/exercise experienced a mean increase in CRP (0.09 mg/dL, 95 % CI: -0.14, 0.33), whereas women who maintained or increased their sports/ exercise experienced a mean decrease in CRP (-0.08 mg/dL, 95 % CI: -0.23, 0.08) (p = 0.046). CONCLUSIONS: Findings from this randomized trial in an ethnically and socio-economically diverse population of pregnant women were consistent with a positive impact of the exercise intervention on CRP levels, but not of statistical significance. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov: NCT00728377 . Registered 2 August 2008.

Impact of an exercise intervention on physical activity during pregnancy: the behaviors affecting baby and you study.

OBJECTIVES: We examined the impact of a prenatal exercise intervention on physical activity in 260 women at risk for gestational diabetes mellitus. METHODS: We randomized participants in the Behaviors Affecting Baby and You (BABY) Study, which took place from 2007 to 2012, to either a 12-week individually tailored, motivationally matched exercise intervention (n=132) or to a comparison health and wellness intervention (n=128). We assessed physical activity with the Pregnancy Physical Activity Questionnaire. We used linear mixed models to evaluate the impact of the interventions on change in physical activity according to intensity and type, total walking, and sedentary behavior. RESULTS: Compared with the health and wellness arm, the exercise arm had significantly greater increases in sports or exercise activity (0.3 vs 5.3 metabolic equivalent of task [MET] hours/week; P<.001), and smaller declines in total activity (-42.7 vs -2.1 MET hours/week; P=.02) and activities of moderate to vigorous intensity (-30.6 vs -10.6 MET hours/week; P=.05), and was more likely to achieve recommended guidelines for physical activity (odds ratio=2.12; 95% confidence interval=1.45, 3.10). CONCLUSIONS: These findings extend the previous literature by demonstrating the benefits of a clinically feasible exercise intervention in an ethnically and socio-economically diverse population. Given the increased risk of adverse maternal health outcomes in ethnic minority groups, these findings may have important implications for reducing health disparities.

The impact of change in physical activity on change in arterial stiffness in overweight or obese sedentary young adults.

Arterial stiffness is associated with cardiovascular events and mortality. Lifestyle factors such as physical activity (PA) may reduce arterial stiffness. The purpose of this study is to determine the impact of change in PA on 1-year change in arterial stiffness in 274 overweight/obese sedentary young adults. The Slow Adverse Vascular Effects of excess weight (SAVE) trial was a study evaluating the relationships between weight loss, dietary sodium, and vascular health. PA was measured with the ActiGraph AM7164 accelerometer. Intensity of activity was determined using established cut-points. Arterial stiffness was assessed by brachial-ankle pulse wave velocity (baPWV) using an automated device. Analysis of covariance compared changes in total accelerometer counts, minutes/day in light-intensity PA (LPA), moderate-to-vigorous PA (MVPA), and sedentary time, by categories of change in baPWV. Models were adjusted for time since baseline visit, age, sex, race, homeostatis model of assessment of insulin resistance, mean arterial pressure, heart rate, and weight change. Total accelerometer counts and time spent in MVPA increased from baseline to 12 months while time spent in LPA significantly decreased. Mean baPWV was similar at each time point. Those who showed decreased baPWV also showed an increase in total accelerometer counts per day and time spent in MVPA in the fully adjusted models (p<0.001). Changes in sedentary time and time spent in LPA were not associated with changes in baPWV. These results indicate that even modest increases in MVPA can reduce arterial stiffness, a risk factor for future cardiovascular events.

Allostatic load in early pregnancy and sleep-disordered breathing.

OBJECTIVES: To assess the association between allostatic load in early pregnancy and sleep-disordered breathing (SDB) during pregnancy. METHODS: High allostatic load in the first trimester was defined as ≥ 4 of 12 biomarkers (systolic blood pressure, diastolic blood pressure, body mass index, cholesterol, low-density lipoprotein, high-density lipoprotein, high sensitivity C-reactive protein, triglycerides, insulin, glucose, creatinine, and albumin) in the unfavorable quartile. SDB was objectively measured using the Embletta-Gold device and operationalized as "SDB ever" in early (6-15 weeks) or mid-pregnancy (22-31 weeks); SDB at each time point was analyzed as secondary outcomes. Multivariable logistic regression was used to test the association between high allostatic load and SDB, adjusted for confounders. Moderation and sensitivity analyses were conducted to assess the role of allostatic load in racial disparities of SDB and obesity affected the relationship between allostatic load and SDB. RESULTS: High allostatic load was present in 35.0% of the nuMoM2b cohort. The prevalence of SDB ever occurred among 8.3% during pregnancy. After adjustment, allostatic load remained significantly associated with SDB ever (aOR= 5.3; 3.6-7.9), in early-pregnancy (aOR= 7.0; 3.8-12.8), and in mid-pregnancy (aOR= 5.8; 3.7-9.1). The association between allostatic load and SDB was not significantly different for people with and without obesity. After excluding BMI from the allostatic load score, the association decreased in magnitude (aOR= 2.6; 1.8-3.9). CONCLUSION: The association between allostatic load and SDB was independent of confounders including BMI. The complex and likely bidirectional relationship between chronic stress and SDB deserves further study in reducing SDB.

Physical activity intensity and cardiovascular risk by ankle-brachial index.

A low ankle-brachial index (ABI) is associated with increased risk for cardiovascular events and mortality. Physical inactivity in individuals with a low ABI may further increase their risk for cardiovascular events. The purpose of this paper is to examine the relationship between the intensity of free-living physical activity and cardiovascular disease (CVD) risk by ABI status. During 2003-2004, the National Health and Nutrition Examination Survey included an accelerometer module and collected ABI data. Individuals were classified as having a normal (1-1.4) or low (< 1) ABI. The Framingham risk score (FRS) was used to determine CVD risk. Multiple linear regression was used to determine the association of total accelerometer counts and time spent at various physical activity intensity levels with FRS by ABI groups. Individuals with a low ABI spent less time engaging in moderate-to-vigorous intensity physical activity (MVPA) (9.1 min/day vs 13.2 min/day; p = 0.06) when compared to those with a normal ABI. There were no differences in light intensity physical activity (LPA) or sedentary behavior between ABI groups. Total accelerometer counts were inversely related to FRS. MVPA, but not LPA, was inversely related to FRS in both normal and low ABI groups (p < 0.001 and p = 0.001, respectively). In conclusion, these findings suggest that even modestly higher levels of physical activity may be beneficial for secondary risk prevention in this high-risk group.

Association between self-reported physical activity and obesity among White, Black, Hispanic, and Asian Americans: 2007 and 2009 brfss.

OBJECTIVE: To examine the association between self-reported leisure-time moderate- to vigorous-intensity physical activity (MVPA) and obesity among non-Hispanic White, non-Hispanic Black, Hispanic, and Asian Americans. METHODS: We analyzed data from 569,816 Whites, 54,521 Blacks, 44,864 Hispanics, and 11,232 Asians aged 18 to 79 years who participated in the 2007 and 2009 Behavioral Risk Factor Surveillance System. Physical activity, height, weight, and demographic data were self-reported through telephone interviews. MVPA level was categorized into inactive, low, medium, and high, and weight status into normal-weight, overweight, and obese based on body mass index. Race/ethnicity-, sex-, and age group-specific polytomous logistic regression analysis was conducted, adjusted for age, education, and income. RESULTS: There was an inverse association between self-reported MVPA and obesity among White men and women (Ps for trend <.0001). Black and Hispanic women also presented an inverse association (Ps for trend <.0001), although the association was weaker compared to White women. In Asians, no association between self-reported MVPA and obesity was observed. CONCLUSIONS: Weak or no association observed between self-reported MVPA and obesity in minority groups may: 1) suggest that other factors than MVPA play more critical roles in determining weight status in minority groups, or 2) reflect large measurement errors of self-report data in minority groups.

Formative Development of ClockWork for the Postpartum Period: A Theory-Based Intervention to Harness the Circadian Timing System to Address Cardiometabolic Health-Related Behaviors.

Individuals with body mass index (BMI) ≥ 25 kg/m2 before pregnancy have greater difficulty losing the weight gained during pregnancy, and this postpartum weight retention predicts higher risk for cardiometabolic disease. The postpartum period involves substantial disruptions in circadian rhythms, including rhythms related to eating, physical activity, sleep, and light/dark exposure, each of which are linked to obesity and cardiometabolic disease in non-pregnant adult humans and animals. We posit that a multi-component, circadian timing system-based behavioral intervention that uses digital tools-ClockWork-will be feasible and acceptable to postpartum individuals and help promote weight- and cardiometabolic health-related behaviors. We provide data from stakeholder interviews with postpartum individuals (pre-pregnancy BMI ≥ 25; n = 7), which were conducted to obtain feedback on and improve the relevance and utility of digital self-monitoring tools for health behaviors and weight during the postpartum period. Participants perceived the ClockWork intervention and digital monitoring app to be helpful for management of postpartum weight-related health behaviors. They provided specific recommendations for increasing the feasibility intervention goals and improving app features for monitoring behaviors. Personalized, easily accessible interventions are needed to promote gestational weight loss after delivery; addressing circadian behaviors is an essential component of such interventions. Future studies will evaluate the efficacy of the ClockWork intervention and associated digital tools for improving cardiometabolic health-related behaviors linked to the circadian timing system during the postpartum period.

Inter-rater reliability of the Infectious Disease Modeling Reproducibility Checklist (IDMRC) as applied to COVID-19 computational modeling research.

Background: Infectious disease computational modeling studies have been widely published during the coronavirus disease 2019 (COVID-19) pandemic, yet they have limited reproducibility. Developed through an iterative testing process with multiple reviewers, the Infectious Disease Modeling Reproducibility Checklist (IDMRC) enumerates the minimal elements necessary to support reproducible infectious disease computational modeling publications. The primary objective of this study was to assess the reliability of the IDMRC and to identify which reproducibility elements were unreported in a sample of COVID-19 computational modeling publications. Methods: Four reviewers used the IDMRC to assess 46 preprint and peer reviewed COVID-19 modeling studies published between March 13th, 2020, and July 31st, 2020. The inter-rater reliability was evaluated by mean percent agreement and Fleiss' kappa coefficients (κ). Papers were ranked based on the average number of reported reproducibility elements, and average proportion of papers that reported each checklist item were tabulated. Results: Questions related to the computational environment (mean κ = 0.90, range = 0.90-0.90), analytical software (mean κ = 0.74, range = 0.68-0.82), model description (mean κ = 0.71, range = 0.58-0.84), model implementation (mean κ = 0.68, range = 0.39-0.86), and experimental protocol (mean κ = 0.63, range = 0.58-0.69) had moderate or greater (κ > 0.41) inter-rater reliability. Questions related to data had the lowest values (mean κ = 0.37, range = 0.23-0.59). Reviewers ranked similar papers in the upper and lower quartiles based on the proportion of reproducibility elements each paper reported. While over 70% of the publications provided data used in their models, less than 30% provided the model implementation. Conclusions: The IDMRC is the first comprehensive, quality-assessed tool for guiding researchers in reporting reproducible infectious disease computational modeling studies. The inter-rater reliability assessment found that most scores were characterized by moderate or greater agreement. These results suggests that the IDMRC might be used to provide reliable assessments of the potential for reproducibility of published infectious disease modeling publications. Results of this evaluation identified opportunities for improvement to the model implementation and data questions that can further improve the reliability of the checklist.

Associations between sleep health and obesity and weight change in adults: The Daily24 Multisite Cohort Study.

OBJECTIVES: To examine cross-sectional and longitudinal associations of individual sleep domains and multidimensional sleep health with current overweight or obesity and 5-year weight change in adults. METHODS: We estimated sleep regularity, quality, timing, onset latency, sleep interruptions, duration, and napping using validated questionnaires. We calculated multidimensional sleep health using a composite score (total number of "good" sleep health indicators) and sleep phenotypes derived from latent class analysis. Logistic regression was used to examine associations between sleep and overweight or obesity. Multinomial regression was used to examine associations between sleep and weight change (gain, loss, or maintenance) over a median of 1.66 years. RESULTS: The sample included 1016 participants with a median age of 52 (IQR = 37-65), who primarily identified as female (78%), White (79%), and college-educated (74%). We identified 3 phenotypes: good, moderate, and poor sleep. More regularity of sleep, sleep quality, and shorter sleep onset latency were associated with 37%, 38%, and 45% lower odds of overweight or obesity, respectively. The addition of each good sleep health dimension was associated with 16% lower adjusted odds of having overweight or obesity. The adjusted odds of overweight or obesity were similar between sleep phenotypes. Sleep, individual or multidimensional sleep health, was not associated with weight change. CONCLUSIONS: Multidimensional sleep health showed cross-sectional, but not longitudinal, associations with overweight or obesity. Future research should advance our understanding of how to assess multidimensional sleep health to understand the relationship between all aspects of sleep health and weight over time.

Mid-pregnancy sleep disturbances are not associated with mid-pregnancy maternal glycemia.

Background: In pregnancy, epidemiological data have consistently shown strong associations between sleep quality and duration and maternal glycemia. However, other sleep disturbances such as difficulty falling asleep and staying asleep are common in pregnancy. They may contribute to impaired maternal glycemia through sympathetic nervous system activity, systemic inflammation, and hormonal pathways. However, there is little research examining associations between these specific sleep disturbances and maternal glycemia. Objective: This study aimed to investigate the associations of sleep disturbances during mid-pregnancy and mid-pregnancy maternal glycemia and gestational diabetes subtypes. Study Design: This is a secondary data analysis of the Comparison of Two Screening Strategies for Gestational Diabetes trial. Participants (n = 828) self-reported the frequency of sleep disturbances (i.e., trouble falling asleep, trouble staying asleep, waking several times per night, and waking feeling tired or worn out) in mid-pregnancy. Gestational diabetes was diagnosed using either the International Associations of Diabetes and Pregnancy Study Groups or Carpenter-Coustan approach. We defined gestational diabetes subtypes based on the degree of insulin resistance and beta-cell dysfunction. We used multinomial logistic regression to examine associations of sleep disturbances with gestational diabetes status (i.e., normal, mild glycemic dysfunction, and gestational diabetes) and gestational diabetes subtypes (i.e., neither insulin resistance or beta-cell dysfunction, insulin resistance only, beta-cell dysfunction only, and insulin resistance and beta-cell dysfunction). Results: A total of 665 participants (80%) had normal glycemia, 81 (10%) mild hyperglycemia, and 80 (10%) had gestational diabetes. Among participants with gestational diabetes, 62 (78%) had both insulin resistance and beta-cell dysfunction, 15 (19 %) had insulin resistance only, and 3 had beta-cell dysfunction only or neither insulin resistance nor beta-cell dysfunction. Sleep disturbance frequency was not associated with maternal glycemia or gestational diabetes subtypes. Conclusions: Sleep disturbances in mid-pregnancy were not associated with maternal glycemia during mid-pregnancy. Future research should collect data on sleep disturbances at multiple time points in pregnancy and in combination with other sleep disturbances to determine whether sleep plays any role in maternal glycemic control.

The association between multidimensional sleep health and gestational weight gain: nuMoM2b Sleep Duration and Continuity Study.

Background: Although poor sleep health is associated with weight gain and obesity in the non-pregnant population, research on the impact of sleep health on weight change among pregnant people using a multidimensional sleep-health framework is needed. This study examined associations among mid-pregnancy sleep health indicators, multidimensional sleep health, and gestational weight gain (GWG). Methods: We conducted a secondary data analysis of the Nulliparous Pregnancy Outcome Study: Monitoring Mothers-to-be Sleep Duration and Continuity Study (n=745). Indicators of individual sleep domains (i.e., regularity, nap duration, timing, efficiency, and duration) were assessed via actigraphy between 16 and 21 weeks of gestation. We defined "healthy" sleep in each domain based on empirical thresholds. Multidimensional sleep health was based on sleep profiles derived from latent class analysis. Total GWG, the difference between self-reported pre-pregnancy weight and the last measured weight before delivery, was converted to z-scores using gestational age- and BMI-specific charts. GWG was defined as low (<-1 SD), moderate (-1 or +1 SD), and high (>+1 SD). Results: Nearly 50% of the participants had a healthy sleep profile (i.e., healthy sleep in most domains), whereas others had a sleep profile defined as having varying degrees of poor health in each domain. While indicators of individual sleep domains were not associated with GWG, multidimensional sleep health was related to low and high GWG. Participants with a sleep profile characterized as having low efficiency, late timing, and long sleep duration (vs. healthy sleep profile) had a higher risk (RR 1.7; 95% CI 1.0, 3.1) of low GWG a lower risk of high GWG (RR 0.5 95% CI 0.2, 1.1) (vs. moderate GWG). Conclusions: Multidimensional sleep health was more strongly associated with GWG than individual sleep domains. Future research should determine whether sleep health is a valuable intervention target for optimizing GWG. Synopsis: Study question: What is the association between mid-pregnancy multidimensional sleep health and gestational weight gain?What's already known?: Sleep is associated with weight and weight gain outside of pregnancyWhat does this study add?: We identified patterns of sleep behaviors associated with an increased risk of low gestational weight gain.