Associations between exposure to phthalates, phenols, and parabens with objective and subjective measures of sleep health among Mexican women in midlife: a cross-sectional and retrospective analysis.

Endocrine-disrupting chemicals (EDCs) may impact sleep during the menopausal transition by altering sex hormones. However, these studies are scarce among Latin American women. This investigation utilized cross-sectional and retrospective data from midlife women enrolled in the Early Life Exposure in Mexico to Environmental Toxicants (ELEMENT) study to examine associations between exposure to EDCs (phthalates, phenols, and parabens) and sleep health measures. For cross-sectional analyses, single spot urine samples were collected between 2017-2019 from a pilot sample of women (N = 91) of midlife age to estimate the urinary concentration of individual phthalates, phenols, and parabens and to calculate the summary concentration of phthalate mixtures. Seven-day nightly sleep duration, midpoint, and fragmentation were obtained from wrist-actigraphy devices and estimated from the actigraphy data using a pruned dynamic programming algorithm. Self-reported poor sleep quality was assessed by one item from the Pittsburgh Sleep Quality Index (PSQI). We examined associations between urinary summary phthalate mixtures, phthalate metabolites, phenol, and paraben analytes with each sleep measure using linear or logistic (to compute odds of poor sleep quality only) regression models adjusted for specific gravity, age, and socioeconomic status. We ran similar regression models for retrospective analyses (N = 74), except that urine exposure biomarker data were collected in 2008 when women were 24-50 years old. At the 2017-2019 midlife visit, 38% reported poor sleep quality. Cross-sectionally, EDCs were associated with longer sleep duration, earlier sleep timing, and more fragmented sleep. For example, every 1-unit IQR increase in the phenol triclosan was associated with a 26.3 min per night (95% CI: 10.5, 42.2; P < 0.05) longer sleep duration and marginally associated with 0.2 decimal hours (95% CI: -0.4, 0.0; P < 0.10) earlier sleep midpoint; while every 1-unit IQR increase in the phthalate metabolite MEHP was associated with 1.1% higher sleep fragmentation (95% CI: 0.1, 2.1; P < 0.05). Retrospective study results generally mirrored cross-sectional results such that EDCs were linked to longer sleep duration, earlier sleep timing, and more fragmented sleep. EDCs were not significantly associated with odds of self-reported poor sleep quality. Results from cross-sectional and retrospective analyses revealed that higher exposure to EDCs was predictive of longer sleep duration, earlier sleep timing, and more fragmented sleep among midlife women.

The Joint Associations of Physical Activity and Sedentary Behaviors on Adiposity during Adolescence: The 1993 Pelotas (Brazil) Cohort Study.

A prior study conducted in high-income countries demonstrated that specific sedentary behavior, such as TV viewing, is prospectively associated with adiposity in both active and inactive adolescents. The aim of this study was to examine the joint associations of sedentary behaviors and moderate- and vigorous-intensity physical activity (MVPA) with adiposity among Brazilian adolescents. This prospective cohort study included 377 participants of the 1993 Pelotas (Brazil) Study who completed an accelerometry assessment at age 13 years and a dual-energy X-ray absorptiometry (DXA) assessment at age 18 years. Accelerometer-measured MVPA was dichotomized into high (≥60 min/day) and low (<60 min/day). Accelerometer-measured sedentary time (SED) was dichotomized into low (<49 min/h) and high (≥49 min/h) based on the median. Self-reported TV viewing time was also dichotomized into low (<3 h/day) and high (≥3 h/day) based on the median. We combined the two MVPA groups (high and low) and two SED groups (low and high) to form the four MVPA&SED groups: high&low, high&high, low&low, and low&high. We also created four MVPA&TV groups in the same manner. Fat mass index (FMI; kg/m2) was calculated using DXA-derived fat mass. Multivariable linear regression analyses compared FMI at 18 years among the four MVPA&SED groups and among the four MVPA&TV groups, adjusting for socioeconomic status, energy intake, and baseline adiposity. The analysis results showed that SED or TV viewing time was not prospectively associated with adiposity in both active and inactive Brazilian adolescents. This study suggests that the association between specific sedentary behaviors, such as TV viewing, and adiposity may differ across societal settings-in this case, high-income vs. middle-income countries.

Diurnal Pain Classification in Critically Ill Patients using Machine Learning on Accelerometry and Analgesic Data.

Quantifying pain in patients admitted to intensive care units (ICUs) is challenging due to the increased prevalence of communication barriers in this patient population. Previous research has posited a positive correlation between pain and physical activity in critically ill patients. In this study, we advance this hypothesis by building machine learning classifiers to examine the ability of accelerometer data collected from daily wearables to predict self-reported pain levels experienced by patients in the ICU. We trained multiple Machine Learning (ML) models, including Logistic Regression, CatBoost, and XG-Boost, on statistical features extracted from the accelerometer data combined with previous pain measurements and patient demographics. Following previous studies that showed a change in pain sensitivity in ICU patients at night, we performed the task of pain classification separately for daytime and nighttime pain reports. In the pain versus no-pain classification setting, logistic regression gave the best classifier in daytime (AUC: 0.72, F1-score: 0.72), and CatBoost gave the best classifier at nighttime (AUC: 0.82, F1-score: 0.82). Performance of logistic regression dropped to 0.61 AUC, 0.62 F1-score (mild vs. moderate pain, nighttime), and CatBoost's performance was similarly affected with 0.61 AUC, 0.60 F1-score (moderate vs. severe pain, daytime). The inclusion of analgesic information benefited the classification between moderate and severe pain. SHAP analysis was conducted to find the most significant features in each setting. It assigned the highest importance to accelerometer-related features on all evaluated settings but also showed the contribution of the other features such as age and medications in specific contexts. In conclusion, accelerometer data combined with patient demographics and previous pain measurements can be used to screen painful from painless episodes in the ICU and can be combined with analgesic information to provide moderate classification between painful episodes of different severities.

Comparação entre processamentos de dados do acelerômetro gt3x+ para atividade física moderada e vigorosa / Comparison between data processing from gt3x+ accelerometer for vigorous and moderate physical activity

RESUMO O uso do acelerômetro para mensurar a atividade física em pesquisas epidemiológicas, apresenta desafios para aumentar a comparabilidade entre os estudos que utilizam esse equipamento. Nesse sentido o objetivo deste trabalho é comparar estimativas de tempo em AFMV para adultos provenientes de diferentes métodos de processamentos de dados, através do acelerômetro Actigraph GT3X+. Trata-se de um estudo transversal, da linha de base do estudo piloto do Estudo Longitudinal dos Determinantes da Atividade Física. Amostra contou com 31 funcionários terceirizados de ambos os sexos, com idade média de 47.05anos (DP=9.35). Os participantes utilizaram acelerômetros do modelo GT3X+ durante sete dias consecutivos. A estimativa de tempo de AFMV foi gerada através de software Actilife e R-package GGIR. Análises estatísticas descritivas, ANOVA e pos-hoc de Bonferroni para comparabilidade foram realizadas no software R. Análise de Bland-Altman foi realizado no SigmaPlot para avaliação de viés e concordância. Houve diferença significativa no tempo médio de AFMV entre os dados baseados em counts e dados brutos (p<0,001). O tempo médio em AFMV foi menor a partir do processamento por dados brutos do que o em counts (-264,81min/dia; p<0,001). Concluindo que os achados sugerem não haver, estatisticamente, equivalência entre os métodos comparados para estimar tempo de AFMV.

ABSTRACT The use of accelerometers to measure physical activity in epidemiological research presents challenges to increase comparability between studies that use this equipment. In this sense, the objective of this work is to compare time estimates in MVPA for adults from different data processing methods, using the Actigraph GT3X+ accelerometer. This is a cross-sectional study, from the baseline of the pilot study of the Longitudinal Study of the Determinants of Physical Activity. Sample had 31 outsourced employees of both genders, with an average age of 47.05 years (SD=9.35). Participants used GT3X+ model accelerometers for seven consecutive days. The MVPA time estimate was generated using Actilife and R-package GGIR software. Descriptive statistical analyses, ANOVA and Bonferroni post-hoc for comparability were performed in the R software. Bland-Altman analysis was performed in SigmaPlot to assess bias and agreement. There was a significant difference in the mean time of MVPA between count-based data and raw data (p<0.001). The average time in MVPA was shorter from processing by raw data than in counts (-264.81 min/day; p<0.001). Concluding that the findings suggest that there is no statistically equivalence between the methods compared to estimate MVPA time.

Validation of SenseWear Armband in children, adolescents, and adults.

SenseWear Armband (SW) is a multisensor monitor to assess physical activity and energy expenditure. Its prediction algorithms have been updated periodically. The aim was to validate SW in children, adolescents, and adults. The most recent SW algorithm 5.2 (SW5.2) and the previous version 2.2 (SW2.2) were evaluated for estimation of energy expenditure during semi-structured activities in 35 children, 31 adolescents, and 36 adults with indirect calorimetry as reference. Energy expenditure estimated from waist-worn ActiGraph GT3X+ data (AG) was used for comparison. Improvements in measurement errors were demonstrated with SW5.2 compared to SW2.2, especially in children and for biking. The overall mean absolute percent error with SW5.2 was 24% in children, 23% in adolescents, and 20% in adults. The error was larger for sitting and standing (23%-32%) and for basketball and biking (19%-35%), compared to walking and running (8%-20%). The overall mean absolute error with AG was 28% in children, 22% in adolescents, and 28% in adults. The absolute percent error for biking was 32%-74% with AG. In general, SW and AG underestimated energy expenditure. However, both methods demonstrated a proportional bias, with increasing underestimation for increasing energy expenditure level, in addition to the large individual error. SW provides measures of energy expenditure level with similar accuracy in children, adolescents, and adults with the improvements in the updated algorithms. Although SW captures biking better than AG, these methods share remaining measurements errors requiring further improvements for accurate measures of physical activity and energy expenditure in clinical and epidemiological research.

Sleep and Lipid Profile During Transition from Childhood to Adolescence.

OBJECTIVES: To assess the longitudinal effects of sleep duration and quality on lipid profiles during the transition from childhood to early adolescence, over a 4-year-period. STUDY DESIGN: A cohort study of children born in 1998 examined at 8 years of age (SD, 0.3; n = 105) and 12 years of age (SD, 0.5; n = 190). Sleep duration, wake after sleep onset, sleep efficiency, and weekend catch-up sleep were measured with actigraphs for 7 (8 years of age) and 8 (12 years of age) nights. Fasting serum samples were collected at 12 years of age. Covariates included age, pubertal development, socioeconomic status, body mass index, and physical activity. RESULTS: In girls, shorter sleep duration at 8 and 12 years of age was associated with lower high-density lipoprotein-cholesterol and higher triglycerides at 12 years of age. Poorer sleep quality at 8 years of age and longer weekend catch-up sleep at 12 years of age was associated with higher triglycerides at 12 years of age. From 8 to 12 years of age, improvement in sleep quality associated with higher total cholesterol, and a decrease in sleep duration with lower lipid levels. In boys, longer sleep duration at 8 years of age, and a larger decrease in sleep duration from 8 to 12 years of age was associated with higher levels of triglycerides at 12 years of age. CONCLUSIONS: Poorer sleep during transition to early adolescence is associated with an atherogenic lipid profile in early adolescent girls, and such effects are less prominent in boys. Poor sleep may have long-term associations with health, which are not mitigated by the amount of physical activity.

Aerobic exercise did not have compensatory effects on physical activity levels in type 2 diabetes patients.

Although exercise promotes beneficial effects in diabetic patients, some studies have questioned the degree of their importance in terms of the increase in total energy expenditure. In these studies, the decrease of physical activity levels (PAL) was referred as "compensatory effect of exercise". However, our aim was to investigate whether aerobic exercise has compensatory effects on PAL in type 2 diabetes patients. Eight volunteers (51.1 ± 8.2 years) were enrolled in a supervised exercise programme for 8 weeks (3 d · wk(-1), 50-60% of VO2 peak for 30-60 min). PAL was measured using tri-axial accelerometers in the 1st, 8th and 12th weeks. Biochemical tests, cardiorespiratory fitness, anthropometric assessment and body composition were measured in the 2nd and 11th weeks. Statistical analysis was performed using non-parametric tests (Friedman and Wilcoxon, P < 0.05). We found no significant differences in PAL between intervention periods, and participants spent the majority of their awake time in sedentary activities. However, the exercise programme generated a significant 14.8% increase in VO2 peak and a 15% reduction in fructosamine. The exercise programme had no compensatory effects on PAL in type 2 diabetes patients, but improved their cardiorespiratory fitness and glycaemic control.

Temporal sleep patterns in adults using actigraph.

The aim of the present study was to characterize the temporal patterns of sleep and wakefulness in a sample of the adult subjects from São Paulo city. All subjects filled the Morningness/Eveningness Questionnaire (MEQ) and wore an actigraph for at least three consecutive days. A total of 359 subjects were considered for the analyses. The mean age was 43±14 years, the mean body mass index was 26.7±5.7 kg/m(2), and 60% were female. The mean MEQ score was 58.0±10.7. The sleep pattern evaluated by the actigraphic analyses showed that 92% had a monophasic sleep pattern, 7% biphasic, and 1% polyphasic sleep pattern. Cluster analysis, based on time to sleep onset, sleep efficiency, sleep latency, and total sleep time, was able to identify three different groups denominated: morning type, evening type, and undefined type. Morning type subjects were more frequent, older, and had higher MEQ scores than evening type subjects. Our results showed that the actigraph objectively assessed the sleep-wake cycle and was able to discriminate between morning and evening type individuals. These findings suggest that the actigraph could be a valuable tool for assessing temporal sleep patterns, including the circadian preferences.