| 141. |
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| 142. |
- Löf, Marie, 1971-, et al.
(författare)
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Hydration of fat-free mass in healthy women with special reference to the effect of pregnancy
- 2004
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Ingår i: American Journal of Clinical Nutrition. - 0002-9165 .- 1938-3207. ; 80:4, s. 960-965
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Tidskriftsartikel (refereegranskat)abstract
- Background: Knowledge of the biological variability of the hydration factor (HF), ie, the ratio between total body water and fat-free mass, is important when calculating total body fat by means of the commonly used two-component model, which is based on estimates of body weight and total body water. The effect of pregnancy on the biological variability of HF, and consequently on the precision of the two-component model, is unknown.Objective: Our goal was to assess the effect of pregnancy on HF and its biological variability.Design: HF was assessed in 33 women planning pregnancy and in 17 of these women during gestational weeks 14 and 32 and 2 wk postpartum. HF was calculated by using estimates of body weight, total body water obtained by means of deuterium dilution, and body volume measured by using underwater weighing.Results: In the 17 women who became pregnant, HF was 0.718 ± 0.023, 0.723 ± 0.031, 0.747 ± 0.017, and 0.734 ± 0.020 before pregnancy, in gestational week 14, in gestational week 32, and 2 wk postpartum, respectively. The biological variability represented ≈2% of average HF in the nonpregnant state. The corresponding figure was >3% in gestational week 14 but ≤1.7% in gestational week 32.Conclusion: The two-component model for assessing body fat is as appropriate during late gestation as it is in the nonpregnant state, although its precision may be impaired when applied during the first part of pregnancy.
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| 143. |
- Löf, Marie, et al.
(författare)
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Impact of diet on breast cancer risk
- 2009
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Ingår i: CURRENT OPINION IN OBSTETRICS and GYNECOLOGY. - 1040-872X .- 1473-656X. ; 21:1, s. 80-85
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Tidskriftsartikel (refereegranskat)abstract
- Purpose of review Breast cancer is the most common female cancer in Western Europe and North America, and becoming an increasing problem in developing countries such as India and China. We review recent studies (published 1 January 2007-31 August 2008) on the impact of diet on breast cancer risk. Recent findings Recent studies have focused on the controversial association for dietary fat and breast cancer as well as the role of newer aspects such as glycemic index, dietary patterns and diet-gene interactions. Evidence that some of the associations may be modified by oestrogen and progesterone receptor status has been presented. Still, only alcohol intake, being overweight and weight gain have shown consistent and strong positive associations with breast cancer risk. The reasons for the null or weak associations often observed regarding diet and breast cancer might be several. For example, there may be no causal association, or existing associations may be masked by measurement error, timing of dietary exposure and differences according to tumour characteristics or diet-gene interactions. Summary Numerous epidemiological studies on diet and breast cancer have been published during our review period. Still, only alcohol intake, being overweight and weight gain have shown consistent and strong positive associations with breast cancer risk.
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| 144. |
- Löf, Marie
(författare)
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Physical activity pattern and activity energy expenditure in healthy pregnant and non-pregnant Swedish women
- 2011
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Ingår i: European Journal of Clinical Nutrition. - : Nature Publishing Group. - 0954-3007 .- 1476-5640. ; 65:12, s. 1295-1301
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Tidskriftsartikel (refereegranskat)abstract
- Background/Objectives: Energy costs of pregnancy approximate 320 MJ in well-nourished women, but whether or not these costs may be partly covered by modifications in activity behavior is incompletely known. In healthy Swedish women: (1) to evaluate the potential of the Intelligent Device for Energy Expenditure and Physical Activity (IDEEA) to assess energy expenditure during free-living conditions, (2) to assess activity pattern, walking pace and energy metabolism in pregnant women and non-pregnant controls, and (3) to assess the effect on energy expenditure caused by changes in physical activity induced by pregnancy. less thanbrgreater than less thanbrgreater thanSubjects/Methods: Activity pattern was assessed using the IDEEA in 18 women in gestational week 32 and in 21 non-pregnant women. Activity energy expenditure (AEE) was assessed using IDEEA, as well as using the doubly labelled water method and indirect calorimetry. less thanbrgreater than less thanbrgreater thanResults: AEE using the IDEEA was correlated with reference estimates in both groups (r = 0.4-0.5; Pandlt;0.05). Reference AEE was 0.9 MJ/24 h lower in pregnant than in non-pregnant women. Pregnant women spent 92 min/24 h more on sitting, lying, reclining and sleeping (P = 0.020), 73 min/24 h less on standing (P = 0.037) and 21 min/24 h less on walking and using stairs (P = 0.049), and walked at a slower pace (1.1 +/- 0.1 m/s versus 1.2 +/- 0.1 m/s; P = 0.014) than did non-pregnant controls. The selection of less demanding activities and slower walking pace decreased energy costs by 720 kJ/24 h and 80 kJ/24 h, respectively. less thanbrgreater than less thanbrgreater thanConclusion: Healthy moderately active Swedish women compensated for the increased energy costs of pregnancy by 0.9 MJ/24 h. The compensation was mainly achieved by selecting less demanding activities.
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| 145. |
- Löf, Marie, 1971-
(författare)
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Studies on energy metabolism and body composition of healthy women before, during and after pregnancy
- 2004
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Current recommendations propose that an entire pregnancy requires an additional amount of energy from the diet equivalent to 335 000 kJ. This figure is mainly based on increases in the basal metabolic rate (BMR) and retention of total body fat (TBF). The BMR response to pregnancy varies considerably among women, but the factors responsible for this variability are unknown. TBF can be calculated from total body water (TBW) and the hydration factor (HF), using the so-called two-component model. However, the validity of this model during pregnancy has been questioned. Furthermore, current recommendations propose that energy needs during pregnancy may be partly offset by reductions in physical activity, but this statement is supported by little experimental evidence. The aims of this thesis were: to evaluate if the physical activity level (PAL) can be estimated by means of heart rate recording, accelerometry, and a questionnaire in women planning pregnancy; to assess the effect of pregnancy on energy expenditure due to physical activity, on activity pattern and on the biological variability of HF; to evaluate the use of bioimpedance spectroscopy (BIS) for assessing TBW during pregnancy; and to identifY factors explaining the variability of the BMR response to pregnancy.Healthy women were studied before pregnancy (n=38), and in gestational weeks 8, 14, 20, 32, 35 and 2 weeks post partum (n=23). Total energy expenditure (TEE), BMR, TEE/BMR, activity pattern, body composition, circulatory variables and serum levels of thyroid hormones and insulin growth factor-I (IGF-1) were measured. Foetal weight in gestational week 31 and infant birth weight were assessed.All estimates of PAL were imprecise and too low in women planning pregnancy. There was little change in TEE/BMR in gestational week 14, but it was significantly reduced in gestational week 32. However, activity pattern was largely unaffected by pregnancy. The biological variability of HF was 2%, 3% and 1.7% or less of average HF before pregnancy and in gestational weeks 14 and 32, respectively. BIS underestimated TBW during pregnancy. In gestational week 14, the increase in BMR correlated significantly with the increase in body weight and with TBF (%)before pregnancy. Together these variables explained about 40% of the variability in the BMR response. In gestational week 32, the increase in BMR correlated significantly with changes in body weight, TBF, fat-free mass, IGF-I, cardiac output and free triiodothyronine. At this stage of gestation the increase in body weight in combination with foetal weight or with the increased levels of IGF-I in serum explained about 60% of the variability of the increased BMR.In conclusion: I) Heart rate recording, accelerometry and the questionnaire produced inappropriate PAL estimates. 2) In women maintaining their pre-pregnant activity pattern the increase in BMR represents the major component of the increased energy expenditure during pregnancy. 3) The two-component model for assessing TBF is appropriate in late gestation, while its precision may be impaired in early pregnancy. 4) BIS in its present form is not appropriate for assessing TBW during pregnancy. 5) Nutritional factors are important regarding the variability in the BMR response to pregnancy.
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| 146. |
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| 147. |
- Löf, Marie, 1971-, et al.
(författare)
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Validation of energy intake by dietary recall against different methods to assess energy expenditure
- 2004
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Ingår i: Journal of human nutrition and dietetics (Print). - 0952-3871 .- 1365-277X. ; 17:5, s. 471-480
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Tidskriftsartikel (refereegranskat)abstract
- Objectives. To compare the validity of dietary recalls and physical activity recalls and investigate some factors influencing this validity. To provide an example showing how procedures based on recalls of physical activity can assess the validity of dietary recalls and identify subjects constantly underreporting their energy intake (EI). Design and subjects. Thirty-seven women were studied using three 24-h dietary recalls, two kinds of physical activity recalls, indirect calorimetry and the doubly labelled water method. Results. The EI obtained using dietary recalls were biased with respect to body mass index (BMI) and attitudes towards body weight and dieting, whereas results obtained using a physical activity recall were not. Eighteen women produced underreports (UR), i.e. their average EI was below 76% of total energy expenditure (TEE), whereas 24 women reported an EI that was lower than TEE on all three recall days, i.e. constantly underreporting subjects. A physical activity recall identified 13 URs and 20 of the constantly underreporting subjects. Conclusions. In contrast to estimates of EI, TEE assessed using physical activity recalls was not biased with respect to BMI or attitudes towards body weight and dieting. Recalls of physical activity represent potentially useful procedures for identifying URs and constantly underreporting subjects but are not accurate enough for individuals.
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| 148. |
- Migueles, Jairo H., et al.
(författare)
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Accelerometer Data Collection and Processing Criteria to Assess Physical Activity and Other Outcomes: A Systematic Review and Practical Considerations
- 2017
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Ingår i: Sports Medicine. - : ADIS INT LTD. - 0112-1642 .- 1179-2035. ; 47:9, s. 1821-1845
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Forskningsöversikt (refereegranskat)abstract
- Background Accelerometers are widely used to measure sedentary time, physical activity, physical activity energy expenditure (PAEE), and sleep-related behaviors, with the ActiGraph being the most frequently used brand by researchers. However, data collection and processing criteria have evolved in a myriad of ways out of the need to answer unique research questions; as a result there is no consensus. Objectives The purpose of this review was to: (1) compile and classify existing studies assessing sedentary time, physical activity, energy expenditure, or sleep using the ActiGraph GT3X/+ through data collection and processing criteria to improve data comparability and (2) review data collection and processing criteria when using GT3X/+ and provide age-specific practical considerations based on the validation/calibration studies identified. Methods Two independent researchers conducted the search in PubMed and Web of Science. We included all original studies in which the GT3X/+ was used in laboratory, controlled, or free-living conditions published from 1 January 2010 to the 31 December 2015. Results The present systematic review provides key information about the following data collection and processing criteria: placement, sampling frequency, filter, epoch length, non-wear-time, what constitutes a valid day and a valid week, cut-points for sedentary time and physical activity intensity classification, and algorithms to estimate PAEE and sleep-related behaviors. The information is organized by age group, since criteria are usually age-specific. Conclusion This review will help researchers and practitioners to make better decisions before (i.e., device placement and sampling frequency) and after (i.e., data processing criteria) data collection using the GT3X/? accelerometer, in order to obtain more valid and comparable data.
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| 149. |
- Migueles, Jairo H., et al.
(författare)
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Accelerometer Data Processing and Energy Expenditure Estimation in Preschoolers
- 2019
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Ingår i: Medicine & Science in Sports & Exercise. - : LIPPINCOTT WILLIAMS & WILKINS. - 0195-9131 .- 1530-0315. ; 51:3, s. 590-598
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Tidskriftsartikel (refereegranskat)abstract
- Purpose To assess the capacity of different acceleration metrics from wrist accelerations to estimate total energy expenditure (TEE) and activity energy expenditure (AEE) using doubly labeled water in preschool children. Methods Thirty-nine preschoolers (5.5 0.1 yr) were included. Total energy expenditure was measured using doubly labeled water during 14 d, and AEE was then calculated using a predicted basal metabolic rate. Participants wore a wGT3X-BT accelerometer on their nondominant wrist for 5 d. We derived the following metrics from raw accelerations: raw ActiGraph activity counts using the normal filter and the low-frequency extension; and alternate summary metrics, such as the Euclidian norm minus 1g (ENMO), Euclidian norm of the high-pass-filtered accelerations (HFEN), the bandpass-filtered accelerations, the HFEN plus Euclidean norm of low-pass filtered accelerations minus 1g (HFEN+) and the mean amplitude deviation. Results Alternate summary metrics explained a larger proportion of the variance in TEE and AEE than ActiGraphs activity counts (counts, 7-8 and 25% of TEE and AEE; alternate summary metrics, 13%-16% and 35%-39% of TEE and AEE). Adjustments for body weight and height resulted in an explanation of 51% of AEE by ENMO. All of the metrics adjusted for fat mass and fat-free mass explained up to 84% and 67% of TEE and AEE, respectively. Conclusions ENMO and the other alternate summary metrics explained more of the variance in TEE and AEE than the ActiGraphs activity counts in 5-yr-old children, suggesting further exploration of these variables in studies on physical activity and energy expenditure in preschoolers. Our results need confirmation in other populations with wider age groups and varying body compositions.
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| 150. |
- Migueles, Jairo H., et al.
(författare)
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Comparability of published cut-points for the assessment of physical activity: Implications for data harmonization
- 2019
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Ingår i: Scandinavian Journal of Medicine and Science in Sports. - : WILEY. - 0905-7188 .- 1600-0838. ; 29:4, s. 566-574
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Tidskriftsartikel (refereegranskat)abstract
- This study aimed to compare estimations of sedentary time (SED) and time spent in physical activity (PA) intensities in children with overweight/obesity across different age-appropriate cut-points based on different body-worn attachment sites and acceleration metrics. A total of 104 overweight/obese children (10.1 +/- 1.1 years old, 43 girls) concurrently wore ActiGraph GT3X+ accelerometers on their right hip and non-dominant wrist for 7 days (24 hours). Euclidean norm -1 g (ENMO) and activity counts from both vertical axis (VACounts) and vector magnitude (VMCounts) were derived. We calculated estimates of SED and light, moderate, vigorous, and moderate-to-vigorous (MVPA) intensity PA using different published cut-points for children. The prevalence of children meeting the recommended 60 min/d of MVPA was calculated. The time spent in SED and the different PA intensities largely differed across cut-points based on different attachment sites and acceleration metrics (ie, SED = 11-252 min/d; light PA = 10-217 min/d; moderate PA = 1-48 min/d; vigorous PA = 1-35 min/d; MVPA = 4-66 min/d). Consequently, the prevalence of children meeting the recommended 60 min/d of MVPA varied from 8% to 96% of the study sample. The present study provides a comprehensive comparison between available cut-points for different attachment and acceleration metrics in children. Furthermore, our data clearly show that it is not possible (and probably will never be) to know the prevalence of meeting the PA guidelines based on accelerometer data since apparent differences range from almost zero to nearly everyone meeting the guidelines.
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