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.

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.

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.

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.

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.

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.

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.

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.

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.

Sleep Health Characteristics among Adults Who Attempted Weight Loss in the Past Year: NHANES 2017-2018.

BACKGROUND: The purpose of this study was to characterize sleep health in adults who attempted weight loss in the prior year. METHODS: We analyzed data from the National Health and Nutrition Examination Survey 2017-2018 exam cycle. We included 4837 US adults who did (n = 1919) or did not (n = 2918) attempt weight loss in the past year. Participants self-reported their sleep regularity, satisfaction, sleepiness, timing, and duration, which we defined as "good" based on the prior literature. We characterized sleep health by weight loss attempts status, current BMI and weight change among participants who attempted weight loss. RESULTS: On average, participants reported good sleep health in 3.21 ± 1.14 out of the five sleep domains. A total of 13% of participants had good sleep health in all five domains. The prevalence of sleep regularity (52%) was lowest, and the prevalence of infrequent sleepiness was highest (72%), relative to other sleep domains. In models adjusting for BMI, sleep health was similar in participants who did and did not attempt weight loss. Among adults who attempted weight loss, good sleep health was inversely associated with current BMI and self-reported weight change. DISCUSSION: This study's findings highlight the importance of considering sleep health when engaging with adults attempting weight loss.

Predictors of Change in Skin Intrinsic Fluorescence in Type 1 Diabetes: The Epidemiology of Diabetes Complications Study.

BACKGROUND: Skin intrinsic fluorescent (SIF) scores are indirect measures of advanced glycation end-products (AGEs). SIF scores are cross-sectionally associated with type 1 diabetes (T1D) complications such as increased albumin excretion rate (AER), coronary artery calcification (CAC) and neuropathy. We assessed predictors of SIF score change in those with T1D. METHODS: Data from the 30-year longitudinal Epidemiology of Diabetes Complications (EDC) study of childhood-onset T1D were used to assess AGEs measured with a SIF score produced by the SCOUT DS® device. SIF scores were assessed twice in 83 participants: between 2007-08 and again between 2010-14. Regression analyses were used to assess independent predictors of SIF score change. RESULTS: At baseline, mean age was 47.9 ± 6.9 years, diabetes duration was 36.7 ± 6.4 years, and median glycosylated hemoglobin (HbA1c) was 7.1 (interquartile range: 6.5, 8.5). During a mean follow-up of 5.2 ± 0.9 years, mean change in SIF score was 2.9 ± 2.8 arbitrary units. In multivariable linear regression models, log HbA1c (P < 0.001), log estimated glomerular filtration rate (eGFR) (P < 0.001), overt nephropathy (defined as AER ≥ 200 µg/min, P = 0.06), and multiple daily insulin shots/pump use (MDI) exposure years (P = 0.02) were independent predictors of SIF score change. CONCLUSIONS: Increases in SIF score over 5 years were related to increased glycemic levels and decreased kidney function (eGFR). MDI and glomerular damage were related to a decreased SIF score. This is one of the first studies with repeated SIF assessments in T1D and provides unique, albeit preliminary, insight about these associations.

Recruitment of veterans from primary care into a physical activity randomized controlled trial: the experience of the VA-STRIDE study.

BACKGROUND: Much of the existing literature on physical activity (PA) interventions involves physically inactive individuals recruited from community settings rather than clinical practice settings. Recruitment of patients into interventions in clinical practice settings is difficult due to limited time available in the clinic, identification of appropriate personnel to efficiently conduct the process, and time-consuming methods of recruitment. The purpose of this report is to describe the approach used to identify and recruit veterans from the Veterans Affairs (VA) Pittsburgh Healthcare System Primary Care Clinic into a randomized controlled PA study. METHODS: A sampling frame of veterans was developed using the VA electronic medical record. During regularly scheduled clinic appointments, primary care providers (PCPs) screened identified patients for safety to engage in moderate-intensity PA and willingness to discuss the study with research staff members. Research staff determined eligibility with a subsequent telephone screening call and scheduled a research study appointment, at which time signed informed consent and baseline measurements were obtained. RESULTS: Of the 3,482 veterans in the sampling frame who were scheduled for a primary care appointment during the study period, 1,990 (57.2%) were seen in the clinic and screened by the PCP; moderate-intensity PA was deemed safe for 1,293 (37.1%), 871 (25.0%) agreed to be contacted for further screening, 334 (9.6%) were eligible for the study, and 232 (6.7%) enrolled. CONCLUSIONS: Using a semiautomated screening approach that combined an electronically-derived sampling frame with paper and pencil prescreening by PCPs and research staff, VA-STRIDE was able to recruit 1 in 15 veterans in the sampling frame. Using this approach, a high proportion of potentially eligible veterans were screened by their PCPs. TRIAL REGISTRATION: Clinical trials.gov identifier: NCT00731094.

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.

Self-reported and accelerometer-derived physical activity levels and coronary artery calcification progression in older women: results from the Healthy Women Study.

OBJECTIVE: Despite the well-supported biological link between physical activity (PA) and atherosclerosis, most previous studies have reported a null association between PA and coronary artery calcification (CAC). The aim of this study was to examine the relationship between PA and CAC progression in 148 Healthy Women Study (HWS) participants over 28 years of observation. METHODS: The HWS was designed to examine cardiovascular risk factor changes from premenopause to postmenopause. Based on CAC scores collected on two follow-up visits (electron beam tomography [EBT] 1 and EBT4) scheduled 12 years apart, participants were classified into one of three groups: (1) no-detectable CAC group (n = 37; 0 CAC on both visits); (2) incident CAC group (n = 46; 0 CAC on the first visit and >0 CAC on the last visit); or (3) prevalent CAC group (n = 65; >0 CAC on both visits). PA data were collected regularly throughout the study using self-report questionnaires and accelerometers on EBT4. RESULTS: The percentage of HWS participants with no detectable CAC decreased from 56.1% on EBT1 to 25.0% on EBT4. Times spent per day in accumulated moderate- to vigorous-intensity PA (MVPA) and bouts of MVPA were each significantly higher in the no-detectable CAC group when compared with the prevalent CAC group (both P ≤ 0.01). After covariate adjustment, these differences remained statistically significant (both P < 0.05). Although self-reported summary estimates collected throughout the study were significantly associated with accelerometer data on EBT4, there were no significant differences in self-reported PA levels by CAC group after covariate adjustment. CONCLUSIONS: Study findings suggest that low levels of accelerometer-derived MVPA may be indicative of subclinical disease in older women.

Effects of weight loss and insulin reduction on arterial stiffness in the SAVE trial.

BACKGROUND: Chronic arterial stiffness contributes to the negative health effects of obesity and insulin resistance, which include hypertension, stroke, and increased cardiovascular and all-cause mortality. Weight loss and improved insulin sensitivity are individually associated with improved central arterial stiffness; however, their combined effects on arterial stiffness are poorly understood. The purpose of this study was to determine how insulin levels modify the improvements in arterial stiffness seen with weight loss in overweight and obese young adults. METHODS: To assess the effects of weight loss and decreased fasting insulin on vascular stiffness, we studied 339 participants in the Slow the Adverse Effects of Vascular Aging (SAVE) trial. At study entry, the participants were aged 20-45, normotensive, non-diabetic, and had a body-mass index of 25-39.9 kg/m2. Measures of pulse wave velocity (PWV) in the central (carotid-femoral (cfPWV)), peripheral (femoral-ankle (faPWV)), and mixed (brachial-ankle (baPWV)) vascular beds were collected at baseline and 6 months. The effects of 6-month change in weight and insulin on measures of PWV were estimated using multivariate regression. RESULTS: After adjustment for baseline risk factors and change in systolic blood pressure, 6-month weight loss and 6-month change in fasting insulin independently predicted improvement in baPWV but not faPWV or cfPWV. There was a significant interaction between 6-month weight change and change in fasting insulin when predicting changes in baPWV (p < 0.001). Individuals experiencing both weight loss and insulin reductions showed the greatest improvement in baPWV. CONCLUSIONS: Young adults with excess weight who both lower their insulin levels and lose weight see the greatest improvement in vascular stiffness. This improvement in vascular stiffness with weight loss and insulin declines may occur throughout the vasculature and may not be limited to individual vascular beds.

Association between physical activity and kidney function: National Health and Nutrition Examination Survey.

INTRODUCTION: Chronic kidney disease is a condition characterized by the deterioration of the kidney's ability to remove waste products from the body. Although treatments to slow the progression of the disease are available, chronic kidney disease may eventually lead to a complete loss of kidney function. Previous studies have shown that physical activities of moderate intensity may have renal benefits. Few studies have examined the effects of total movement on kidney function. The purpose of this study was to determine the association between time spent at all levels of physical activity intensity and sedentary behavior and kidney function. METHODS: Data were obtained from the 2003-2004 and 2005-2006 National Health and Nutrition Examination Survey, a cross-sectional study of a complex, multistage probability sample of the US population. Physical activity was assessed using an accelerometer and questionnaire. Glomerular filtration rate (eGFR) was estimated using the Modification of Diet in Renal Disease study formula. To assess linear associations between levels of physical activity and sedentary behavior with log-transformed estimated GFR (eGFR), linear regression was used. RESULTS: In general, physical activity (light and total) was related to log eGFR in females and males. For females, the association between light and total physical activity with log eGFR was consistent regardless of diabetes status. For males, the association between light and total physical activity and log eGFR was only significant in males without diabetes. CONCLUSIONS: When examining the association between physical activity, measured objectively with an accelerometer, and kidney function, total and light physical activities were found to be positively associated with kidney function.

Objectively measured physical activity of USA adults by sex, age, and racial/ethnic groups: a cross-sectional study.

BACKGROUND: Accelerometers were incorporated in the 2003-2004 National Health and Nutritional Examination Survey (NHANES) study cycle for objective assessment of physical activity. This is the first time that objective physical activity data are available on a nationally representative sample of U.S. residents. The use of accelerometers allows researchers to measure total physical activity, including light intensity and unstructured activities, which may be a better predictor of health outcomes than structured activity alone. The aim of this study was to examine objectively determined physical activity levels by sex, age and racial/ethnic groups in a national sample of U.S. adults. METHODS: Data were obtained from the 2003-2004 NHANES, a cross-sectional study of a complex, multistage probability sample of the U.S. population. Physical activity was assessed with the Actigraph AM-7164 accelerometer for seven days following an examination. 2,688 U.S. adults with valid accelerometer data (i.e. at least four days with at least 10 hours of wear-time) were included in the analysis. Mean daily total physical activity counts, as well as counts accumulated in minutes of light, and moderate-vigorous intensity physical activity are presented by sex across age and racial/ethnic groups. Generalized linear modeling using the log link function was performed to compare physical activity in sex and racial/ethnic groups adjusting for age. RESULTS: Physical activity decreases with age for both men and women across all racial/ethnic groups with men being more active than women, with the exception of Hispanic women. Hispanic women are more active at middle age (40-59 years) compared to younger or older age and not significantly less active than men in middle or older age groups (i.e. age 40-59 or age 60 and older). Hispanic men accumulate more total and light intensity physical activity counts than their white and black counterparts for all age groups. CONCLUSION: Physical activity levels measured objectively by accelerometer demonstrated that Hispanic men are, in general, more active than their white and black counterparts. This appears to be in contrast to self-reported physical activity previously reported in the literature and identifies the need to use objective measures in situations where the contribution of light intensity and/or unstructured physical activity cannot be assumed homogenous across the populations of interest.