Changes in Body Weight and Waist Circumference Affect Incident Hypercholesterolemia During 7 Years of Follow‐up

Objective: To assess whether changes in total and regional adiposity affect the odds for becoming hypercholesterolemic. Methods and Procedures: Changes in BMI and waist circumference were compared to self‐reported physician‐diagnosed hypercholesterolemia in 24,397 men and 10,023 women followed prospectively in the National Runners' Health Study. Results: Incident hypercholesterolemia were reported by 3,054 men and 519 women during (mean ± s.d.) 7.8 ± 1.8 and 7.5 ± 2.0 years of follow‐up, respectively. Despite being active, men's BMI increased by 1.15 ± 1.71 kg/m² and women's BMI increased by 0.96 ± 1.89 kg/m². The odds for developing hypercholesterolemia increased significantly in association with gains in BMI and waist circumferences in both sexes. A gain in BMI ≥2.4 kg/m² significantly (P < 0.0001) increased the odds for hypercholesterolemia by 94% in men and 129% in women compared to those whose BMI declined (40 and 76%, respectively, adjusted for average of the baseline and follow‐up BMI, P < 0.0001). A gain of ≥6 cm in waist circumference increased men's odds for hypercholesterolemia by 74% (P < 0.0001) and women's odds by 70% (P < 0.0001) relative to those whose circumference declined (odds increased 40% at P < 0.0001 and 49% at P < 0.01, respectively adjusted for average circumference). BMI and waist circumference at the end of follow‐up were significantly associated (P < 0.0001) with the log odds for hypercholesterolemia in both men (e.g., coefficient ± s.e.: 0.115 ± 0.011 per kg/m²) and women (e.g., 0.119 ± 0.019 per kg/m²) when adjusted for baseline values, whereas baseline BMI and circumferences were unrelated to the log odds when adjusted for follow‐up values. Discussion: These observations are consistent with the hypothesis that weight gain acutely increases the risk for hypercholesterolemia.     

Alcohol Intake and 8‐Year Weight Gain in Women: A Prospective Study

Objective: To examine prospectively the relationship between alcohol and 8‐year weight gain in women. Research Methods and Procedures: A prospective study of 49, 324 women 27 to 44 years old who did not have a history of cardiovascular disease, cancer, or diabetes, who were not pregnant during the study period, and who reported weights in 1991 and 1999. Results: In cross‐sectional analyses, there was a significant inverse relationship between alcohol and BMI even after adjustment for dietary factors and a wide range of confounders. In multivariate prospective analyses, a nonlinear relationship was seen between alcohol and weight gain (≥5 kg) in all women. Compared with nondrinkers, the adjusted relative odds [95% confidence interval (CI)] of weight gain according to grams per day were 0.94 (0.89, 0.99) for those consuming 0.1 to 4.9 g/d, 0.92 (0.85, 0.99) for 5 to 14.9 g/d, 0.86 (0.76, 0.78) for 15 to 29.9 g/d, and 1.07 (0.89, 1.28) for those consuming 30+ g/d (p < 0.0001 for quadratic trend). Women who continued to drink heavily and those who became heavy drinkers showed similar increased odds of weight gain. The increased odds of weight gain associated with heavy drinking (30+ g/d) were most marked in the younger women (<35 years) (odds ratio 1.64; 5% CI 1.03 to 2.61). In African‐American women, light drinking was associated with increased odds of weight gain compared with nondrinkers (odds ratio = 2.43; 95% CI 1.22 to 4.82) Discussion: Our data suggest that light to moderate drinking (up to 30 g/d) is not associated with weight gain in women except possibly in African‐American women. Heavier drinking may promote weight gain in women.     

Eating Frequency is Associated With Energy Intake but Not Obesity in Midlife Women

Midlife women tend to gain weight with age, thus increasing risk of chronic disease. The purpose of this study was to examine associations between overweight/obesity and behavioral factors, including eating frequency, in a cross‐sectional national sample of midlife women (n = 1,099) (mean age = 49.7 years, and BMI = 27.7 kg/m²). Eating behaviors and food and nutrient intakes were based on a mailed 1‐day food record. BMI was calculated from self‐reported height and weight, and level of physical activity was assessed by self‐reported questionnaire. After exclusion of low‐energy reporters (32% of sample), eating frequency was not associated with overweight/obesity (P > 0.05) and was not different between BMI groups (normal, 5.21 ± 1.79; overweight, 5.16 ± 1.74; obese, 5.12 ± 1.68, P = 0.769). Adjusted logistic regression showed that eating frequency, snacking frequency, breakfast consumption, eating after 10 pm and consuming meals with children or other adults were not significantly associated with overweight/obesity. Total energy intake increased as eating frequency increased in all BMI groups, however, obese women had greater energy intake compared to normal weight women who consumed the same number of meals and snacks. Intake of fruit and vegetables, whole grains, dietary fiber, dairy, and added sugars also increased as eating frequency increased. While eating frequency was not associated with overweight/obesity, it was associated with energy intake. Thus, addressing total energy intake rather than eating frequency may be more appropriate to prevent weight gain among midlife women.     

Inflammation Markers Predict Increased Weight Gain in Smoking Quitters

Objective: Undesirable weight gain often follows smoking cessation. We investigated whether weight gain after smoking cessation is greater in those with higher levels of inflammatory markers. Research Methods and Procedures: We studied weight gain and risk of a large gain (≥90th percentile) over 3 years in a cohort study of 11, 687 U.S. men and women, 45 to 64 years old, with focus on the 2664 who continued and the 493 who quit smoking. Results: Among new quitters, adjusted weight gain for those in the highest (vs. lowest) quartile of leukocytes was 0.56 kg/yr more (95% confidence interval, 0.17 to 0.95); for those in the highest (vs. lowest) quartile of fibrinogen, 0.60 kg/yr more (95% confidence interval, 0.27 to 0.92; p = 0.02 and 0.001 for adjusted smoking status by leukocyte and smoking status by fibrinogen interaction terms, respectively). In adjusted analyses, the odds ratio for a large gain associated with quitting (vs. continuing) was 6.2 for those in the highest quartile of leukocytes vs. 2.2 for those in the lowest leukocyte quartile (p = 0.03 for smoking status by inflammatory marker interaction). Similarly, the odds ratio for a large gain associated with quitting was 4.5 in the highest fibrinogen quartile vs. 2.5 in the lowest (p = 0. 09 for the interaction term). Discussion: Weight gain after smoking cessation is increased in those with higher baseline levels of leukocytes and fibrinogen. These findings suggest a close relationship between inflammatory mediators and regulators of energy balance that may have important clinical implications.     

Risk Profiles for Weight Gain among Postmenopausal Women: A Classification and Regression Tree Analysis Approach

Purpose

Risk factors for obesity and weight gain are typically evaluated individually while “adjusting for” the influence of other confounding factors, and few studies, if any, have created risk profiles by clustering risk factors. We identified subgroups of postmenopausal women homogeneous in their clustered modifiable and non-modifiable risk factors for gaining ≥ 3% weight.

Methods

This study included 612 postmenopausal women 50–79 years old, enrolled in an ancillary study of the Women''s Health Initiative Observational Study between February 1995 and July 1998. Classification and regression tree and stepwise regression models were built and compared.

Results

Of 27 selected variables, the factors significantly related to ≥ 3% weight gain were weight change in the past 2 years, age at menopause, dietary fiber, fat, alcohol intake, and smoking. In women younger than 65 years, less than 4 kg weight change in the past 2 years sufficiently reduced risk of ≥ 3% weight gain. Different combinations of risk factors related to weight gain were reported for subgroups of women: women 65 years or older (essential factor: < 9.8 g/day dietary factor), African Americans (essential factor: currently smoking), and white women (essential factor: ≥ 5 kg weight change for the past 2 years).

Conclusions

Our findings suggest specific characteristics for particular subgroups of postmenopausal women that may be useful for identifying those at risk for weight gain. The study results may be useful for targeting efforts to promote strategies to reduce the risk of obesity and weight gain in subgroups of postmenopausal women and maximize the effect of weight control by decreasing obesity-relevant adverse health outcomes.     

Nut consumption and weight gain in a Mediterranean cohort: The SUN study

Objective: To assess the association, in a Mediterranean population, between nut consumption and risk of weight gain (at least 5 kg) or the risk of becoming overweight/obese. Research Methods and Procedures: The Seguimiento Universidad de Navarra project is a prospective cohort of 8865 adult men and women who completed a follow‐up questionnaire after a median of 28 months. Dietary habits were assessed with a previously validated semiquantitative food‐frequency questionnaire. Results: Nine hundred thirty‐seven participants reported a weight gain of ≥5 kg at follow‐up. After adjusting for age, sex, smoking, leisure time physical activity, and other known risk factors for obesity, participants who ate nuts two or more times per week had a significantly lower risk of weight gain (odds ratio: 0.69; 95% confidence interval: 0.53 to 0.90, p for trend = 0.006) than those who never or almost never ate nuts. Participants with little nut consumption (never/almost never) gained an average of 424 grams (95% confidence interval: 102 to 746) more than frequent nut eaters. Nut consumption was not significantly associated with incident overweight/obesity in the cohort. Discussion: Frequent nut consumption was associated with a reduced risk of weight gain (5 kg or more). These results support the recommendation of nut consumption as an important component of a cardioprotective diet and also allay fears of possible weight gain.     

Do Energy Density and Dietary Fiber Influence Subsequent 5‐Year Weight Changes in Adult Men and Women?

Objective: We examined whether associations between dietary components and, in particular, energy density (ED) predicted subsequent 5‐year weight changes. Research Methods and Procedures: The present longitudinal population study was part of the Danish World Health Organization Multinational Monitoring of Trends and Determinants in Cardiovascular Disease (MONICA) and the 1936 cohort dietary studies. Effects of components were studied in relation to subsequent 5‐year weight changes in 862 men and 900 women, 30 to 60 years old. Linear multiple regression analyses were conducted. Results: Mean 5‐year changes in body weight (BW) were 1.2 ± 3.9 and 1.3 ± 4.6 kg for men and women, respectively. In general, neither ED nor any of the dietary components was associated with subsequent change in BW. In women, ED was positively associated with weight gain among the obese (BMI > 30 kg/m²) and inversely associated with weight gain in normal‐weight women (BMI < 25 kg/m²) (p = 0.01). However, in men there was a non‐ significant inverse trend between ED and weight gain in the obese and no significant interaction. Discussion: To our knowledge, this is the first prospective study to examine the associations between ED and subsequent changes in BW, and despite a general belief that ED is a major determinant of obesity, the present study did not generally lend support for an association. However, among certain subgroups, an energy‐dense diet may be a risk factor for weight development.     

The Relationship between Body Mass Index and Post-Cessation Weight Gain in the Year after Quitting Smoking: A Cross-Sectional Study

Introduction

There is wide variability in the amount of weight gained when quitting smoking, but little is known about key predictors of weight gain. We examined the impact of body mass index (BMI) category and sociodemographic variables on post-cessation weight gain.

Materials and Methods

We utilized National Health and Nutrition Examination Survey data from five consecutive cycles of data collection from 2003–2004 to 2011–2012 to estimate post-cessation weight gain by BMI category among recent quitters (n = 654). We analyzed data on their “current weight” and their “past year weight”. We also compared the recent quitters with current smokers, in order to estimate the amount of weight that could be attributed to quitting smoking.

Results

Recent quitters gained 1.4 kg (95% CI: 0.8 to 2.0), while current smokers had a non-significant weight change (-0.01 kg (95% CI: -0.3 to 0.2). Weight gain was significant for those in the normal weight (3.1 kg, 95% CI: 2.3 to 3.9) and overweight BMI categories (2.2 kg, 95% CI: 1.1 to 3.2).

Conclusions

BMI category is a key factor in the extent of post-cessation weight gain, with normal and overweight recent quitters gaining significant amounts of weight.     

Sitting Time Is Associated With Weight,but Not With Weight Gain in Mid‐Aged Australian Women

The aim of this study was to examine the associations between sitting time, weight, and weight gain in Australian women born in 1946–1951. Data were from 8,233 women who completed surveys for the Australian Longitudinal Study on Women's Health (ALSWH) in 2001, 2004, and 2007. Associations between sitting time and weight, and between sitting time and weight change in each 3‐year period were examined using repeated measures modeling. The associations between weight and change in sitting time were also examined. Analyses were stratified for BMI categories: normal weight (18.5 ≤ BMI < 25), overweight (25 ≤ BMI < 30), and obese (BMI ≥ 30). In cross‐sectional models, each additional hour of sitting time was associated with 110 g (95% confidence interval (CI): 40–180) and 260 g (95% CI: 140–380) additional weight in overweight and obese women, respectively (fully adjusted model). In prospective analyses, sitting time was not consistently associated with weight change, after adjustment for other variables, and weight was not associated with change in sitting time over successive 3‐year periods. In conclusion, although the cross‐sectional associations between sitting time and weight were evident in overweight and obese women, there was no consistent association between sitting time and weight gain. A potential explanation is that prospective associations may only be apparent over longer periods of time. These results do not support a role for reducing sitting time as a short‐term means of weight control in mid‐aged women.     

Retinal vessel diameters and obesity: a population-based study in older persons

Objective: Obesity is linked with large vessel atherosclerosis and diabetes. Its association with microvascular changes is less clear. We investigated the associations among retinal vessel diameters, vessel wall signs, and BMI in an older population. Research Methods and Procedures: Retinal photographs were taken on 3654 persons aged 49+ years at baseline of the Blue Mountains Eye Study in Australia. Arteriolar and venular diameters were measured from digitized retinal photographs of the right eyes. BMI was calculated as weight (kilograms)/height (meters²). Incident obesity was defined in persons with BMI ≤ 30 at baseline but >30 after 5 years. A significant weight gain was defined as an increase in BMI of 2+ SDs (4 or more units) over the 5‐year period. Results: At baseline, mean BMI was 26.1 (±4.6) in this population. At 5‐year examinations, 177 (10.0% of 1773 at risk) developed incident obesity, and 136 (6.4% of 2143 at risk) had significant weight gain. After adjusting for age, sex, smoking, triglyceride levels, and mean arterial blood pressure, persons with wider retinal venular diameters had a higher risk of incident obesity (odds ratio, 1.8; 95% confidence interval, 1.0 to 3.1, comparing the highest with lowest venular diameter quintiles) and significant weight gain (odds ratio, 1.7; 95% confidence interval, 0.9 to 3.2). These associations were attenuated with further adjustment for baseline BMI. Arteriolar diameter was unrelated with baseline or change in BMI. Discussion: Wider retinal venular diameter is associated with risk of obesity, independent of hypertension, diabetes, lipids, and cigarette smoking. These data may support a role for impaired microvascular function in the course of weight gain.     

Maternal Obesity and Infant Heart Defects

Objective: This study determined whether obese women have an increased risk of cardiovascular defects in their offspring compared with average weight women. Research Methods and Procedures: In a case‐control study, prospectively collected information was obtained from Swedish medical health registers. The study included 6801 women who had infants with a cardiovascular defect and, as controls, all delivered women (N = 812, 457) during the study period (1992 to 2001). Infants with chromosomal anomalies or whose mothers had pre‐existing diabetes were excluded. Obesity was defined as BMI >29 kg/m², and morbid obesity was defined as BMI >35 kg/m². Comparisons were made with average weight women (BMI = 19.8 to 26 kg/m²). Results: In the group of obese mothers, there was an increased risk for cardiovascular defects compared with the average weight mothers [adjusted odds ratio (OR) = 1.18; 95% CI, 1.09 to 1.27], which was slightly more pronounced for the severe types of cardiovascular defects (adjusted OR = 1.23; 95% CI, 1.05 to 1.44). With morbid obesity, the OR for cardiovascular defects was 1.40 (95% CI, 1.22 to 1.64), and for severe cardiovascular defects, the OR was 1.69 (95% CI, 1.27 to 2.26). There was an increased risk for all specific defects studied among the obese women, but only ventricular septal defects and atrial septal defects reached statistical significance. Discussion: In this sample, a positive association was found between maternal obesity in early pregnancy and congenital heart defects in the offspring. A suggested explanation is undetected type 2 diabetes in early pregnancy, but other explanations may exist.     

A Prospective Study of the Effect of Childbearing on Weight Gain in African‐American Women

Objective: To prospectively assess the influence of bearing a first, second, or later child on weight gain among African‐American women in the context of other risk factors. Research Methods and Procedures: Data were obtained in a prospective follow‐up study of African‐American women from across the U.S. who are participants in the Black Women's Health Study. Postal questionnaires were used to collect baseline data in 1995 and follow‐up data in 1997 and 1999. Parous and nulliparous women (11, 196) (21 to 39 years old at baseline), of whom 1230 had a singleton birth during follow‐up, are the subjects of the present analyses. We assessed change in BMI (kilograms per meter squared) in relation to childbearing during 4 years of follow‐up, with use of multivariable linear regression to control for important risk factors. Results: During 4 years of follow‐up, the BMI of participants increased by an average of 1.6 kg/m², equivalent to a weight gain of ～4.4 kg. Women who had a child during follow‐up gained more weight than women who remained nulliparous, and those who had a first child gained more than those who had a second or later child. The weight gain associated with childbearing increased with increasing baseline BMI and was appreciable among heavier women. For example, among women with a baseline index of 36, the increase in BMI for women who bore a first child was 1.1 kg/m² more than that of nulliparous women, equivalent to a difference in weight gain of ～3.0 kg. Discussion: Childbearing is an important contributor to weight gain among African‐American women.     

Sedentary behavior, recreational physical activity, and 7-year weight gain among postmenopausal U.S. women

Objective: To assess the relationship among recreational physical activity (PA), non‐occupational sedentary behavior, and 7‐year weight gain among postmenopausal U.S. women 40 to 69 years old. Research Methods and Procedures: In 1992 and 1999, 18,583 healthy female participants from the Cancer Prevention Study II Nutrition Cohort completed questionnaires on anthropometric characteristics and lifestyle factors. The associations between recreational PA [in metabolic equivalent (MET) hours per week] and non‐occupational sedentary behavior (in hours per day) at baseline and risk for 7‐year weight gain (5 to 9 or ≥10 vs. ±4 pounds) were assessed using multivariate logistic regression analysis. Results: Neither PA nor sedentary behavior was associated with a 5‐ to 9‐pound weight gain. Among women who were not overweight at baseline (BMI <25.0), the odds of ≥10‐pound weight gain were 12% lower (odds ratio, 0.88; 95% confidence interval, 0.77 to 0.99) for those in the highest category of recreational PA (≥18 MET h/wk) compared with >0 to <4 MET h/wk; odds were 47% higher (odds ratio, 1.47; 95% confidence interval, 1.21 to 1.79) for non‐overweight women who reported ≥6 h/d of non‐occupational sedentary behavior compared with <3 h/d. Neither PA nor sedentary behavior were associated with risk of ≥10‐pound weight gain weight among women who were overweight at baseline (BMI ≥25.0). Discussion: Both recreational PA and non‐occupational sedentary behavior independently predicted risk of ≥10‐pound weight gain among postmenopausal women who were not overweight at baseline. Public health messages to prevent weight gain among normal‐weight postmenopausal women may need to focus on decreasing time spent in sedentary behaviors and increasing the amount of time spent on PA.     

Weight maintenance 2 years after participation in a weight loss program promoting low-energy density foods

Objective: Observational study designed to determine weight outcomes and associated dietary intake patterns for a sample of participants ≥1 year after completing the University of Alabama at Birmingham EatRight Weight Management Program. Research Methods and Procedures: Seventy‐four former participants (64% women) completed follow‐up visits ≥1 year after participating in EatRight, which promotes low‐energy density, high‐complex carbohydrate foods. Weight maintenance was defined as gaining <5% of body weight since completion of the EatRight program and staying below their program entry weight. Those who gained ≥5% of their body weight since completion were classified as gainers. Results: During EatRight, participants of the follow‐up study lost an average of 4.0 kg. After a mean follow‐up time of 2.2 years, the average weight change was +0.59 kg (mean BMI, 32.5 kg/m²). Seventy‐eight percent of participants gained <5% of their body weight; 46% had no weight regain or continued weight loss. Unadjusted mean intake for maintainers was 1608 kcal, whereas calorie intake for gainers was 1989 kcal. Despite eating slightly fewer calories (adjusted difference, 244; p = 0.058), maintainers ate a similar amount of food, resulting in a lower energy‐density pattern (p = 0.016) compared with those who regained ≥5% of body weight. Gainers also reported consuming larger portions of several food groups. Discussion: Our results indicate that low‐energy‐density eating habits are associated with long‐term weight maintenance. Those who maintain weight after the EatRight program consume a low‐energy‐density dietary pattern and smaller portions of food groups potentially high in energy density than those who regain weight.     

Role of Weight History on Functional Limitations and Disability in Late Adulthood: The ARIC Study

Objective: To examine associations of weight history with functional limitations and disability in white and African‐American men and women. Research Methods and Procedures: Data were from the Atherosclerosis Risk in Communities study (n = 11, 177). Associations of recalled weight status at age 25 and weight change from age 25 to ages 45 to 64 with functional limitations, activities of daily living (ADLs), and instrumental activities of daily living (IADLs) at follow‐up (ages 52 to 75) were examined using logistic regression. Results: Obesity (BMI ≥ 30 kg/m²) at age 25 was associated with functional limitations and ADL and IADL impairment at follow‐up in white and African‐American men and women. For example, obese compared with normal weight (BMI, 18.5 to 24.9 kg/m²) white women had higher odds of mild [odds ratio (95% confidence interval), 1.97 (1.18 to 3.29)] and severe [9.81 (5.92 to 16.27)] functional limitations and ADL [3.48 (2.36 to 5.13)] and IADL [2.95 (2.00 to 4.33)] impairment. In African‐American women, obesity was associated with higher odds of mild [2.71 (1.14 to 6.41)] and severe [6.01 (2.53 to 14.26)] functional limitations and ADL [1.82 (1.10 to 3.00)] and IADL [2.39 (1.47 to 3.90)] impairment. Similar associations were found in men. Compared with weight maintenance (±10 lbs), large weight gain (>30 lbs) from age 25 to ages 45 to 64 was also associated with functional limitations and ADL and IADL impairment in white and African‐American men and women. Discussion: Maintenance of a healthy body weight throughout adulthood may play a role in preventing or delaying the onset of functional limitations and disability, resulting in increased quality of life and decreased health care costs.     

Association of childhood sexual abuse with obesity in a community sample of lesbians

Objective: Our goal was to examine the association between childhood sexual abuse (CSA) and obesity in a community‐based sample of self‐identified lesbians. Research Methods and Procedures: A diverse sample of women who self‐identified as lesbian was recruited from the greater Chicago metropolitan area. Women (n = 416) were interviewed about sexual abuse experiences that occurred before the age of 18. Self‐reported height and weight were used to calculate BMI and categorize women as normal‐weight (<25.0 kg/m²), overweight (25.0 to 29.9 kg/m²), obese (30.0 to 39.9 kg/m²), or severely obese (≥40 kg/m²). The relationship between CSA and BMI was examined using multinomial logistic regression analysis. Results: Overall, 31% of women in the sample reported CSA, and 57% had BMI ≥25.0 kg/m². Mean BMI was 27.8 (±7.2) kg/m² and was significantly higher among women who reported CSA than among those who did not report CSA (29.4 vs. 27.1, p < 0.01). CSA was significantly related to weight status; 39% of women who reported CSA compared with 25% of women who did not report CSA were obese (p = 0.004). After adjusting for age, race/ethnicity, and education, women who reported CSA were more likely to be obese (odds ratio, 1.9; 95% confidence interval, 1.1–3.4) or severely obese (odds ratio, 2.3; 95% confidence interval, 1.1–5.2). Discussion: Our findings, in conjunction with the available literature, suggest that CSA may be an important risk factor for obesity. Understanding CSA as a factor that may contribute to weight gain or act as a barrier to weight loss or maintenance in lesbians, a high‐risk group for both CSA and obesity, is important for developing successful obesity interventions for this group of women.     

BMI and headache among women: results from 11 epidemiologic datasets

Objective: To evaluate the association between BMI (kg/m²) and headaches among women. Methods and Procedures: Cross‐sectional analysis of 11 datasets identified after searching for all large publicly available epidemiologic cohort study datasets containing relevant variables. Datasets included National Health Interview Survey (NHIS): 1997–2003, the first National Health Examination and Nutrition Survey, Alameda County Health Study (ACHS), Tecumseh Community Health Study (TCHS), and Women's Health Initiative (WHI). The women (220,370 in total) were aged 18 years or older and had reported their headache or migraine status. Results: Using nonlinear regression techniques and models adjusted for age, race, and smoking, we found that increased BMI was generally associated with increased likelihood of headache or severe headache among women. A BMI of ～20 was associated with the lowest risk of headache. Relative to a BMI of 20, mild obesity (BMI of 30) was associated with roughly a 35% increase in the odds for experiencing headache whereas severe obesity (BMI of 40) was associated with roughly an 80% increase in odds. Results were essentially unchanged when models were further adjusted for socioeconomic variables, alcohol consumption, and hypertension. Being diagnosed with migraine showed no association with BMI. Discussion: Among US women, a BMI of ～20 (about the 5th percentile) was associated with the lowest likelihood of headache. Consistently across studies, obese women had significantly increased risk for headache. By contrast, the risk for diagnosed migraine headache per se was not obviously related to BMI. The direction of causation and mechanisms of action remain to be determined.     

Relationship of BMI,Waist Circumference,and Weight Change with Use of Health Services by Older Adults

Objective: To examine the relationship of BMI, waist circumference (WC), and weight change with use of health care services by older adults. Research Methods and Procedures: This was a prospective cohort study conducted from 2001 to 2003 among 2919 persons representative of the non‐institutionalized Spanish population ≥60 years of age. Analyses were performed using logistic regression, with adjustment for age, educational level, size of place of residence, tobacco use, alcohol consumption, and presence of chronic disease. Results: Obesity (BMI ≥ 30 kg/m²) and abdominal obesity (WC >102 cm in men and >88 cm in women) in 2001 were associated with greater use of certain health care services among men and women in the period 2001–2003. Compared with women with WC ≤ 88 cm, women with abdominal obesity were more likely to visit primary care physicians [odds ratio (OR): 1.36; 95% confidence limit (CL): 1.06–1.73] and receive influenza vaccination (OR: 1.30; 95% CL: 1.03–1.63). Weight gain was not associated with greater health service use by either sex, regardless of baseline BMI. Weight loss was associated with greater health service use by obese and non‐obese subjects of both sexes. In comparison with those who reported no important weight change, non‐obese women who lost weight were more likely to visit hospital specialists (OR: 1.45; 95% CL: 1.02–2.06), receive home medical visits (OR: 1.61; 95% CL: 1.06–2.45), be hospitalized (OR: 1.88; 95% CL: 1.29–2.74), and have more than one hospital admission (OR: 2.31; 95% CL: 1.19–4.47). Discussion: Obesity and weight loss are associated with greater health service use among the elderly.     

Hysterectomy is associated with postmenopausal body composition characteristics

The impact of hysterectomy without oophorectomy and with no malignant purpose on body composition and postmenopausal weight gain was tested in 184 Viennese females aged between 47 and 57 years (mean 52.9). Hysterectomized women were significantly heavier than those who experienced a spontaneous menopause (controls). The amount of fat tissue, especially in the abdominal region, was significantly higher in hysterectomized women. Furthermore, they were reported to have experienced a significantly higher weight gain since menopause (9.1 versus 6.0 kg). No significant differences in bone mass were found. Psychological stress factors and hormonal changes following hysterectomy are discussed as possible causes of these differences.     

Weight cycling and 6-year weight change in healthy adults: The Aerobics Center Longitudinal Study

Objective: To determine the longitudinal relationship between a reported history of weight cycling and the trajectory of weight in a group of normal‐weight to obese women and men. Research Methods and Procedures: This was a clinic‐based cohort study conducted over 6 years. Subjects were healthy women (n = 141) and men (n = 797) age 20 to 78 years who completed at least four comprehensive medical exams at the Cooper Clinic (Dallas, TX) between 1987 and 2003. Weight loss history was reported, and body weight was measured at all examinations. Weight cycling status was derived from weight loss history and defined as ≥five episodes of weight loss of ≥2.3 kg/episode. Using linear mixed effects models, weight at each examination was regressed on weight cycling status separately for women and men while controlling for selected covariables. Results: Baseline BMI was 23 and 21 kg/m² among cycling and non‐cycling women and was 27 and 25 kg/m² among cycling and non‐cycling men, respectively. We observed a non‐significant difference (p = 0.09) in women by cycling status (average weight gain = 0.5 and 0.2 kg/yr among cyclers and non‐cyclers, respectively) and no difference in weight gain over time among men by cycling status (average weight gain = 0.2 kg/yr among both groups, p = 0.99). Higher baseline cardiorespiratory fitness level and increased fitness over the follow‐up were associated with attenuated weight gain in both women and men. Discussion: In healthy, middle‐aged individuals, a history of weight cycling does not seem to increase the risk of long‐term weight gain in men; however, this relation needs to be studied further in women.