Medical Hazards of Obesity

Pi‐Sunyer, F. Xavier

doi:10.7326/0003-4819-119-7_part_2-199310011-00006

Cited by 1,165 publications

(630 citation statements)

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“…Due to increased risk of pregnancy complications and obesity in offspring [5][6][7][8][9][10], women of childbearing age need efficacious and accessible lifestyle interventions [11,12]. Evidencebased lifestyle interventions have not had broad reach due to high cost and patient and provider burden [13].…”

Section: Introductionmentioning

confidence: 99%

Interest in a Twitter-delivered weight loss program among women of childbearing age

Waring

Schneider

Appelhans

et al. 2015

Behav. Med. Pract. Policy Res.

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Weight management through the childbearing years is important, yet few women have access to efficacious weight loss programs. Online social network-delivered programs may increase reach and thus impact. The aim of this study was to gauge interest in a Twitter-based weight loss intervention among women of childbearing age and the feasibility of recruitment via Twitter. We recruited English-speaking women aged 18-45 years (N = 63) from Twitter to complete an anonymous online survey including open-ended questions about program advantages and concerns. Forty percent of participants were obese and 83 % were trying to lose weight. Eighty-one percent were interested in a Twitter-delivered weight loss program. Interest was high in all subgroups (62-100 %). Participants (59 %) cited program advantages, including convenience, support/accountability, and privacy. Concerns (59 %) included questions about privacy, support/accountability, engagement, efficacy, and technology barriers. Research is needed to develop and evaluate social media-delivered interventions, and to develop methods for recruiting participants directly from Twitter.

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Section: Introductionmentioning

confidence: 99%

Interest in a Twitter-delivered weight loss program among women of childbearing age

Waring

Schneider

Appelhans

et al. 2015

Behav. Med. Pract. Policy Res.

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“…[1][2][3] Obesity is a risk factor for many physical diseases, such as type 2 diabetes 4 and cardiovascular diseases, 5 and can lead to premature death. 6 Especially abdominal obesity, as estimated by the waist-to-hip ratio (WHR), is associated with type 2 diabetes mellitus, cardiovascular disease and stroke.…”

Section: Introductionmentioning

confidence: 99%

Obesity and depression: results from the longitudinal Northern Finland 1966 Birth Cohort Study

et al. 2005

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Objective: To examine the association between body size and depression in a longitudinal setting and to explore the connection between obesity and depression in young adults at the age of 31 years. Design: This study forms part of the longitudinal Northern Finland 1966 Birth Cohort Study (N ¼ 12 058). The follow-up studies were performed at 14 and 31 years. Data were collected by postal inquiry at 14 years and by postal inquiry and clinical examination at 31 years. Subjects: A total of 8451 subjects (4029 men and 4422 women) who gave a written informed consent and information on depression by three depression indicators at 31 years. Measurements: Body size at 14 (body mass index (BMI) and 31 (BMI and waist-to-hip ratio (WHR)) years and depression at 31 years by three different ways: depressive symptoms by the HSCL-25-depression questionnaire (HSCL-25), the use of antidepressants and self-reported physician-diagnosed depression. Results: Obesity at 14 years associated with depressive symptoms at 31 years; among male subjects using the cutoff point 2.01 in the HSCL-25 (adjusted odds ratio (OR) 1.97, 95% CI 1.06-3.68), among female subjects using the cutoff point 1.75 (adjusted OR 1.64, 95% CI 1.16-2.32). Female subjects who were obese both at baseline and follow-up had depressive symptoms relatively commonly (adjusted OR 1.40, 95% CI 1.06-1.85 at cutoff point 1.75); a similar association was not found among male subjects. The proportion of those who used antidepressants was 2.17-fold higher among female subjects who had gained weight compared to female subjects who had stayed normal-weighted (adjusted OR 2.17, 95% CI 1.28-3.68). In the crosssectional analyses male subjects with abdominal obesity (WHR X85th percentile) had a 1.76-fold risk of depressive symptoms using the cutoff 2.01 in the HSCL-25 (adjusted OR 1.76, 95% CI 1.08-2.88). Abdominally obese male subjects had a 2.07-fold risk for physician-diagnosed depression (adjusted OR 2.07, 95% CI 1.23-3.47) and the proportion of those who used antidepressants was 2.63-fold higher among obese male subjects than among male subjects without abdominal obesity (adjusted OR 2.63, 95% CI 1.33-5.21). Abdominal obesity did not associate with depression in female subjects. Conclusion: Obesity in adolescence may be associated with later depression in young adulthood, abdominal obesity among male subjects may be closely related to concomitant depression, and being overweight/obese both in adolescence and adulthood may be a risk for depression among female subjects.

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“…[3][4][5][6] Obesity develops when energy intake exceeds energy expenditure for a prolonged period of time. In free-living humans, activity related energy expenditure is the most variable component of total energy expenditure.…”

Section: Introductionmentioning

confidence: 99%

Body composition is associated with physical activity in daily life as measured using a triaxial accelerometer in both men and women

Hoed

2008

Int J Obes

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Background: Activity-related energy expenditure is the most variable component of total energy expenditure and thus an important determinant of energy balance. Objective: To determine whether body composition is related to physical activity in both men and women. Design: A total of 134 healthy participants were recruited (80 women, 54 men; aged 21 ± 2 years; body mass index, 22.0 ± 2.4). Physical activity was measured for a period of 2 weeks using a triaxial accelerometer for movement registration (Tracmor). Percentage body fat (%BF) was determined by underwater weighing and deuterium dilution according to Siri's threecompartment model. Results: The participant characteristicsFbody mass, height and gender together explained a substantial part of the variation in %BF (R 2 ¼ 0.75, SEE ¼ 4.0%). Adding physical activity to the model increased the explained variation in %BF with 4% (R 2 ¼ 0.79, SEE ¼ 3.7%, Po0.001). Taking seasonality into account by adding the number of daylight hours as an independent variable further increased the explained variation with 1% (R 2 ¼ 0.80, SEE ¼ 3.7%, Po0.05). In analogy, the association was evaluated for both genders separately. In women, %BF and physical activity were significantly associated (Po0.001). In men, %BF was only associated with physical activity when seasonality was taken into account as well (Po0.05). This probably resulted from men participating more in season bound sports, because an association was found without adjusting for seasonality when only men with a consistent year-round participation in sports were considered. Conclusion: Evidence was found for an association between body composition and physical activity in both genders. A consistent year-round degree of physical activity appears to be a prerequisite to reveal the association. Moreover, Tracmorassessed physical activity improves the estimate of %BF when a participant's characteristics are taken into account.

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Medical Hazards of Obesity

Cited by 1,165 publications

References 0 publications

Interest in a Twitter-delivered weight loss program among women of childbearing age

Interest in a Twitter-delivered weight loss program among women of childbearing age

Obesity and depression: results from the longitudinal Northern Finland 1966 Birth Cohort Study

Body composition is associated with physical activity in daily life as measured using a triaxial accelerometer in both men and women

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