192 resultados para excessive pregnancy weight gain


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Obesity and diabetes in Israeli sand rats, Psammomys obesus, occur with the sequential transition of animals from normal insulin sensitivity to impaired insulin sensitivity, accompanied by increased adiposity, prior to insulin resistance and obesity, in a manner similar to susceptible human populations. The current study was designed to examine the role of de novo lipid synthesis in the development of excessive weight gain in P. obesus. Sand rats were classified at 12 wk of age into three groups: A, normoglycemic normoinsulinemic; B, normoglycemic hyperinsulinemic; C, hyperglycemic hyperinsulinemic, based on glucose and insulin responses in fed sand rats. Body weight, liver weight, white adipose tissue (WAT) mass and food intake were significantly elevated in Group C compared to Group A (P < 0.05). Lipogenic rate was measured by the amount of 3H incorporated into subscapular brown adipose tissue (BAT), epidiymal WAT and liver per hour, from sand rats with and without access to food. No difference in lipogenic rate was found between the groups in BAT, indicating that this tissue is of minor importance in whole body lipogenesis in P. obesus. In the WAT there was a greater lipogenic rate with the development of obesity and hyperinsulinemia (Group B vs. Group A) but no difference in the liver. However, the onset of hyperglycemia (Group C) further stimulated WAT lipogenesis and initiated increased hepatic lipogenesis, both of which contributed to the pre-existing obesity. This study suggests that elevated lipogenesis is not the primary cause of obesity in P. obesus, as lipogenic rate only markedly increases after obesity is already present in hyperglycemic animals.

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Almost half of Australian women of child-bearing age are overweight or obese, with a rate of 30–50% reported in early pregnancy. Maternal adiposity is a costly challenge for Australian obstetric care, with associated serious maternal and neonatal complications. Excess gestational weight gain is an important predictor of offspring adiposity into adulthood and higher maternal weight later in life. Current public health and perinatal care approaches in Australia do not adequately address excess perinatal maternal weight or gestational weight gain. This paper argues that the failure of primary health-care providers to offer systematic advice and support regarding women’s weight and related lifestyle behaviours in child-bearing years is an outstanding ‘missed opportunity’ for prevention of inter-generational overweight and obesity. Barriers to action could be addressed through greater attention to: clinical guidelines for maternal weight management for the perinatal period, training and support of maternal health-care providers to develop skills and confidence in raising weight issues with women, a variety of weight management programs provided by state maternal health services, and clear referral pathways to them. Attention is also required to service systems that clearly define roles in maternal weight management and ensure consistency and continuity of support across the perinatal period.

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Objective
Emerging evidence suggests that psychosocial stress may influence weight gain. The relationship between stress and weight change and whether this was influenced by demographic and behavioral factors was explored.

Design and Methods
A total of 5,118 participants of AusDiab were prospectively followed from 2000 to 2005. The relationship between stress at baseline and BMI change was assessed using linear regression.

Results
Among those who maintained/gained weight, individuals with high levels of perceived stress at baseline experienced a 0.20 kg/m2 (95% CI: 0.07-0.33) greater mean change in BMI compared with those with low stress. Additionally, individuals who experienced 2 or ≥3 stressful life events had a 0.13 kg/m2 (0.00-0.26) and 0.26 kg/m2 (0.14-0.38) greater increase in BMI compared with people with none. These relationships differed by age, smoking, and baseline BMI. Further, those with multiple sources of stressors were at the greatest risk of weight gain.

Conclusion
Psychosocial stress, including both perceived stress and life events stress, was positively associated with weight gain but not weight loss. These associations varied by age, smoking, obesity, and multiple sources of stressors. Future treatment and interventions for overweight and obese people should consider the psychosocial factors that may influence weight gain.

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Background: The implementation of healthy school canteen policies has been recommended as a strategy to help prevent unhealthy eating and excessive weight gain. Internationally, research suggests that schools often fail to implement practices consistent with healthy school canteen policies. Without a population wide implementation, the potential benefits of these policies will not be realised. The aim of this trial is to assess the effectiveness of an implementation intervention in increasing school canteen practices consistent with a healthy canteen policy of the New South Wales (NSW), Australia, government known as the 'Fresh Tastes @ School NSW Healthy School Canteen Strategy'.Methods/design: The parallel randomised trial will be conducted in 70 primary schools located in the Hunter region of New South Wales, Australia. Schools will be eligible to participate if they are not currently meeting key components of the healthy canteen policy. Schools will be randomly allocated after baseline data collection in a 1:1 ratio to either an intervention or control group using a computerised random number function in Microsoft Excel. Thirty-five schools will be selected to receive a multi-component intervention including implementation support from research staff, staff training, resources, recognition and incentives, consensus and leadership strategies, follow-up support and implementation feedback. The 35 schools allocated to the control group will not receive any intervention support as part of the research trial. The primary outcome measures will be i) the proportion of schools with a canteen menu that does not contain foods or beverages restricted from regular sale ('red' and 'banned' items) and ii) the proportion of schools where healthy canteen items ('green' items) represent the majority (>50%) of products listed on the menu. Outcome data will be collected via a comprehensive menu audit, conducted by dietitians blind to group allocation. Intervention effectiveness will be assessed using logistic regression models adjusting for baseline values.Discussion: The proposed trial will represent a novel contribution to the literature, being the first randomised trial internationally to examine the effectiveness of an intervention to facilitate implementation of a healthy canteen policy.

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Post-partum weight loss is critical to preventing and managing obesity in women, but the results from lifestyle interventions are variable and the components associated with successful outcomes are not yet clearly identified. This study aimed to identify lifestyle intervention strategies associated with weight loss in post-partum women. MEDLINE, EMBASE, PubMed, CINAHL and four other databases were searched for lifestyle intervention studies (diet or exercise or both) in post-partum women (within 12 months of delivery) published up to July 2014. The primary outcome was weight loss. Subgroup analyses were conducted for self-monitoring, individual or group setting, intervention duration, intervention types, the use of technology as a support, and home- or centre-based interventions. From 12,673 studies, 46 studies were included in systematic review and 32 randomized controlled trials were eligible for meta-analysis (1,892 women, age 24-36 years). Studies with self-monitoring had significantly greater weight lost than those without (-4.61 kg [-7.08, -2.15] vs. -1.34 kg [-1.66, -1.02], P = 0.01 for subgroup differences). Diet and physical activity when combined were significantly more effective on weight loss compared with physical activity alone (-3.24 kg [-4.59, -1.90] vs. -1.63 kg [-2.16, -1.10], P < 0.001 for subgroup differences). Lifestyle interventions that use self-monitoring and take a combined diet-and-exercise approach have significantly greater weight loss in post-partum women.

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INTRODUCTION: Early childhood is an important period for establishing behaviours that will affect weight gain and health across the life course. Early feeding choices, including breast and/or formula, timing of introduction of solids, physical activity and electronic media use among infants and young children are considered likely determinants of childhood obesity. Parents play a primary role in shaping these behaviours through parental modelling, feeding styles, and the food and physical activity environments provided. Children from low socio-economic backgrounds have higher rates of obesity, making early intervention particularly important. However, such families are often more difficult to reach and may be less likely to participate in traditional programs that support healthy behaviours. Parents across all socio-demographic groups frequently access primary health care (PHC) services, including nurses in community health services and general medical practices, providing unparalleled opportunity for engagement to influence family behaviours. One emerging and promising area that might maximise engagement at a low cost is the provision of support for healthy parenting through electronic media such as the Internet or smart phones. The Growing healthy study explores the feasibility of delivering such support via primary health care services.

METHODS: This paper describes the Growing healthy study, a non-randomised quasi experimental study examining the feasibility of an intervention delivered via a smartphone app (or website) for parents living in socioeconomically disadvantaged areas, for promoting infant feeding and parenting behaviours that promote healthy rather than excessive weight gain. Participants will be recruited via their primary health care practitioner and followed until their infant is 9 months old. Data will be collected via web-based questionnaires and the data collected inherently by the app itself.

ETHICS AND DISSEMINATION: This study received approval from the University of Technology Sydney Ethics committee and will be disseminated via peer-reviewed publications and conference presentations.

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A range of important early-life predictors of later obesity have been identified. Children of lower socioeconomic position (SEP) have a steeper weight gain trajectory from birth with a strong socioeconomic gradient in child and adult obesity prevalence. An assessment of the association between SEP and the early-life predictors of obesity has been lacking. The review involved a two-stage process: Part 1, using previously published systematic reviews, we developed a list of the potentially modifiable determinants of obesity observable in the pre-natal, peri-natal or post-natal (pre-school) periods; and part 2, conducting a literature review of evidence for socioeconomic patterning in the determinants identified in part 1. Strong evidence was found for an inverse relationship between SEP and (1) pre-natal risk factors (pre-pregnancy maternal body mass index (BMI), diabetes and pre-pregnancy diet), (2) antenatal/peri natal risk factors (smoking during pregnancy and low birth weight) and (3) early-life nutrition (including breastfeeding initiation and duration, early introduction of solids, maternal and infant diet quality, and some aspects of the home food environment), and television viewing in young children. Less strong evidence (because of a lack of studies for some factors) was found for paternal BMI, maternal weight gain during pregnancy, child sleep duration, high birth weight and lack of physical activity in young children. A strong socioeconomic gradient exists for the majority of the early-life predictors of obesity suggesting that the die is cast very early in life (even pre-conception). Lifestyle interventions targeting disadvantaged women at or before child-bearing age may therefore be particularly important in reducing inequality. Given the likely challenges of reaching this target population, it may be that during pregnancy and their child's early years are more feasible windows for engagement.

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Objectives

To examine relationships between body mass index (BMI), prevalence of physician-recorded cardiovascular disease (CVD) risk factors in primary care, and changes in risk with 10% weight change.

Methods

The Counterweight Project conducted a baseline cross-sectional survey of medical records of 6150 obese (BMI ≥ 30 kg/m2), 1150 age- and sex-matched overweight (BMI 25 to <30 kg/m2), and 1150 age- and sex-matched normal weight (BMI 18.5 to <25 kg/m2) controls, in primary care. Data were collected for the previous 18 months to examine BMI and disease prevalence, and then modelled to show the potential effect of 10% weight loss or gain on risk.

Results

Obese patients develop more CVD risk factors than normal weight controls. BMI ≥ 40 kg/m2 exhibits increased prevalence of type 2 diabetes mellitus (DM), odds ratio (OR) men: 6.16 (p < 0.001); women: 7.82 (p < 0.001) and hypertension OR men: 5.51 (p < 0.001); women: 4.16 (p < 0.001). Dyslipidaemia peaked around BMI 35 to <37.5 kg/m2, OR men: 3.26 (p < 0.001); women 3.76 (p < 0.001) and CVD at BMI 37.5 to <40 kg/m2 in men, OR 4.48 (p < 0.001) and BMI ≥ 40 kg/m2 in women, OR 3.98 (p < 0.001).

A 10% weight loss from the sample mean of 32.5 kg/m2 reduced the OR for type 2 DM by 30% and CVD by 20%, while 10% weight gain increased type 2 DM risk by more than 35% and CVD by 20%.

Conclusion

Obesity plays a fundamental role in CVD risk, which is reduced with weight loss. Weight management intervention strategies should be a public health priority to reduce the burden of disease in the population.

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Background:  As obesity prevalence and health-care costs increase, Health Care providers must prevent and manage obesity cost-effectively.

Methods:  Using the 2006 NICE obesity health economic model, a primary care weight management programme (Counterweight) was analysed, evaluating costs and outcomes associated with weight gain for three obesity-related conditions (type 2 diabetes, coronary heart disease, colon cancer). Sensitivity analyses examined different scenarios of weight loss and background (untreated) weight gain.

Results:  Mean weight changes in Counterweight attenders was −3 kg and −2.3 kg at 12 and 24 months, both 4 kg below the expected 1 kg/year background weight gain. Counterweight delivery cost was £59.83 per patient entered. Even assuming drop-outs/non-attenders at 12 months (55%) lost no weight and gained at the background rate, Counterweight was ‘dominant’ (cost-saving) under ‘base-case scenario’, where 12-month achieved weight loss was entirely regained over the next 2 years, returning to the expected background weight gain of 1 kg/year. Quality-adjusted Life-Year cost was £2017 where background weight gain was limited to 0.5 kg/year, and £2651 at 0.3 kg/year. Under a ‘best-case scenario’, where weights of 12-month-attenders were assumed thereafter to rise at the background rate, 4 kg below non-intervention trajectory (very close to the observed weight change), Counterweight remained ‘dominant’ with background weight gains 1 kg, 0.5 kg or 0.3 kg/year.

Conclusion:  Weight management for obesity in primary care is highly cost-effective even considering only three clinical consequences. Reduced healthcare resources use could offset the total cost of providing the Counterweight Programme, as well as bringing multiple health and Quality of Life benefits.

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Objectives Prescribed medications represent a high and increasing proportion of UK health care funds. Our aim was to quantify the influence of body mass index (BMI) on prescribing costs, and then the potential savings attached to implementing a weight management intervention.

Methods Paper and computer-based medical records were reviewed for all drug prescriptions over an 18-month period for 3400 randomly selected adult patients (18–75 years) stratified by BMI, from 23 primary care practices in seven UK regions. Drug costs from the British National Formulary at the time of the review were used. Multivariate regression analysis was applied to estimate the cost for all drugs and the ‘top ten’ drugs at each BMI point. This allowed the total and attributable prescribing costs to be estimated at any BMI. Weight loss outcomes achieved in a weight management programme (Counterweight) were used to model potential effects of weight change on drug costs. Anticipated savings were then compared with the cost programme delivery. Analysis was carried out on patients with follow-up data at 12 and 24 months as well as on an intention-to-treat basis. Outcomes from Counterweight were based on the observed lost to follow-up rate of 50%, and the assumption that those patients would continue a generally observed weight gain of 1 kg per year from baseline.

Results The minimum annual cost of all drug prescriptions at BMI 20 kg/m2 was £50.71 for men and £62.59 for women. Costs were greater by £5.27 (men) and £4.20 (women) for each unit increase in BMI, to a BMI of 25 (men £77.04, women £78.91), then by £7.78 and £5.53, respectively, to BMI 30 (men £115.93 women £111.23), then by £8.27 and £4.95 to BMI 40 (men £198.66, women £160.73). The relationship between increasing BMI and costs for the top ten drugs was more pronounced. Minimum costs were at a BMI of 20 (men £8.45, women £7.80), substantially greater at BMI 30 (men £23.98, women £16.72) and highest at BMI 40 (men £63.59, women £27.16). Attributable cost of overweight and obesity accounted for 23% of spending on all drugs with 16% attributable to obesity. The cost of the programme was estimated to be approximately £60 per patient entered. Modelling weight reductions achieved by the Counterweight weight management programme would potentially reduce prescribing costs by £6.35 (men) and £3.75 (women) or around 8% of programme costs at one year, and by £12.58 and £8.70, respectively, or 18% of programme costs after two years of intervention. Potential savings would be increased to around 22% of the cost of the programme at year one with full patient retention and follow-up.

Conclusion Drug prescriptions rise from a minimum at BMI of 20 kg/m2 and steeply above BMI 30 kg/m2. An effective weight management programme in primary care could potentially reduce prescription costs and lead to substantial cost avoidance, such that at least 8% of the programme delivery cost would be recouped from prescribing savings alone in the first year.

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ObjectiveThis study aimed to describe the changes in weight and waist circumference (WC), examine the incidence of obesity as defined by body mass index (BMI) and WC, and describe the changes in the prevalence of obesity over 12 years.MethodsIn 1999/2000, 11,247 adults aged ≥25 years were recruited from 42 randomly selected areas across Australia. In total, 44.6% of eligible participants completed follow-up in 2011/12. Height, weight, and WC were measured at both surveys.ResultsPeople who were 25–34 years of age at baseline gained an average of 6.7 kg weight and 6.6 cm WC, whereas those aged ≥75 years lost an average of 4.5 kg and gained an average of 0.8 cm. Women had a greater increase in WC than men, but did not differ in terms of weight gain. The 12-year incidence of obesity was 15.0% when defined by BMI and 31.8% when defined by WC. According to BMI and WC combined, the percentage of the cohort that was normal weight decreased from 33 to 21% and the percentage that was obese increased from 32 to 49% between baseline and 2012.ConclusionsIn addition to BMI, assessment of WC should be incorporated more frequently when assessing population trends of obesity and the burden of disease associated with excess adiposity.

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Background: Young women are at high risk of weight gain yet few studies have examined the long-term effectiveness of weight loss programs in this group. This study aimed to investigate the effects of a self-directed internet-based lifestyle program on body weight in young women.

Methods: Overweight or obese young women (BMI 33.4 ± 0.3 kg/m2, age 27.8 ± 0.3 years) were initially randomized to General lifestyle advice (G) or Structured lifestyle advice (S) via in-person and website support for 12 weeks (Phase I). After Phase I, all participants were supported through a self-directed internet-based program for 36 weeks (Phase II). The internet-based program included a structured hypocaloric diet, physical activity program, self-monitoring tools, peer group forum and monthly emails. Body weight, energy intake and physical activity were measured at week 0, week 12, week 24 and week 48. Adherence to self-regulatory behaviors was measured at week 48. Mixed model analyses were conducted to determine changes in body weight, energy intake and physical activity.

Results: A total of 203 overweight or obese young women commenced Phase I and 130 commenced Phase II. In Phase I, S group had significantly greater weight loss than G group (4.2 ± 0.6 kg vs 0.6 ± 0.3 kg, P<0.001). In Phase II, both groups had significant weight loss over time without significant group differences (-0.8 ± 1.1kg vs -0.8 ± 0.6, P>0.05). Forty-one percent (53/130) of the participants who commenced Phase II completed the internet-based intervention. Dropouts had a higher baseline BMI, were more likely to be married or in a de facto relationship, and more likely to have at least one child.

Conclusions: A self-directed internet-based program could be effective in providing support in maintaining weight loss on a structured lifestyle program in young women over 36 weeks. Further research is required to maintain engagement in young women who were married/in a de facto relationship or have children.

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OBJECTIVE: To identify predictors of increased adiposity for different measures of adiposity. DESIGN: Prospective cohort study, the Melbourne Collaborative Cohort Study (MCCS), with data at baseline (1990-1994) and wave 2 (2003-2007). SETTING: Participants recruited from the community. SUBJECTS: Australian-born participants (n 5879) aged 40 to 69 years who were not current smokers and who were free from common chronic diseases at recruitment. At baseline and at wave 2, weight and waist circumference were measured; while demographic and lifestyle variables were obtained at baseline via structured interviews. RESULTS: Participants who reported any recreational physical activity at baseline had lower weight and smaller waist circumference at wave 2 than those who did not, particularly for younger participants and for vigorous physical activity. Walking for leisure was not associated, and greater physical activity at work was associated, with greater adiposity measures at wave 2. A diet low in carbohydrates and fibre, but high in fat and protein, predicted greater weight and waist circumference at wave 2. Participants were less likely to have elevated weight or waist circumference at wave 2 if they consumed low to moderate amounts of alcohol. CONCLUSIONS: Our findings indicate that promoting vigorous physical activity, encouraging a diet high in carbohydrate and fibre but low in fat and protein, and limiting alcohol intake could be promising approaches for preventing obesity in middle-aged adults. Similar interventions should successfully address the management of both weight and waist circumference, as they were predicted by similar factors.

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This study examined the relationship between normal weight, overweight and obesity class I and II+, and the risk of disability, which is defined as impairment in activities of daily living (ADL). Systematic searching of the literature identified eight cross-sectional studies and four longitudinal studies that were comparable for meta-analysis. An additional four cross-sectional studies and one longitudinal study were included for qualitative review. Results from the meta-analysis of cross-sectional studies revealed a graded increase in the risk of ADL limitations from overweight (1.04, 95% confidence interval [CI] 1.00-1.08), class I obesity (1.16, 95% CI 1.11-1.21) and class II+ obesity (1.76, 95% CI 1.28-2.41), relative to normal weight. Meta-analyses of longitudinal studies revealed a similar graded relationship; however, the magnitude of this relationship was slightly greater for all body mass index categories. Qualitative analysis of studies that met the inclusion criteria but were not compatible for meta-analysis supported the pooled results. No studies identified met all of the pre-defined quality criteria, and subgroup analysis was inhibited due to insufficient comparable studies. We conclude that increasing body weight increases the risk of disability in a graded manner, but also emphasize the need for additional studies using contemporary longitudinal cohorts with large numbers of obese class III individuals, a range of ages and with measured height and weight, and incident ADL questions.