Karen E Remsberg

Ohio University, Athens, OH, United States

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Publications (11)48.48 Total impact

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    ABSTRACT: To evaluate the effects of habitual physical activity (PA) on the metabolic syndrome (MS) in young adult men and women. Cross-sectional PA data were utilized from 249 women and 237 men, aged 18-40 years in the Fels Longitudinal Study. MS components--abdominal circumference (AC), triglycerides (TG), HDL, blood pressure (BP), and fasting glucose (FG)--were dichotomized according to the National Cholesterol Education Program's Adult Treatment Panel III revised criteria. Leisure, sport, work, and total PA scores were calculated using the Baecke Questionnaire of Habitual Physical Activity. Multiple logistic regression modeling assessed the effects of PA, age, smoking, and BMI on MS status. 26.9% of men and 19.3% of women had MS. For men, MS risk was reduced with increases in both total PA [OR = 0.65 (95% CI: 0.47, 0.90)] and sport PA [OR = 0.40 (95% CI: 0.23, 0.70)]. AC, TG, and HDL values also improved with total and sport PA. Among women, the risk for MS was marginally reduced by total PA [OR = 0.72 (95% CI: 0.50, 1.02)] and HDL levels were increased by both total PA [OR = 0.79 (95% CI: 0.63, 0.98)] and sport PA [OR = 0.54 (95% CI: 0.35, 0.84)]. Increased total and sport PA reduces risk for the MS in young men, though not as clearly in young women.
    American Journal of Human Biology 07/2007; 19(4):544-50. · 2.34 Impact Factor
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    ABSTRACT: Given the considerable time and research cost of analyzing biomedical images to quantify adipose tissue volumes, automated image analysis methods are highly desirable. Hippo Fat is a new software program designed to automatically quantify adipose tissue areas from magnetic resonance images without user inputs. Hippo Fat has yet to be independently validated against commonly used image analysis software programs. Our aim was to compare estimates of VAT (visceral adipose tissue) and SAT (subcutaneous adipose tissue) using the new Hippo Fat software against those from a widely used, validated, computer-assisted manual method (slice-O-matic version 4.2, Tomovision, Montreal, CA, USA) to assess its potential utility for large-scale studies. A Siemens Magnetom Vision 1.5-T whole-body scanner and a T1-weighted fast-spin echo pulse sequence were used to collect multiple, contiguous axial images of the abdomen from a sample of 40 healthy adults (20 men) aged 18-77 years of age, with mean body mass index of 29 kg/m(2) (range=19-43 kg/m(2)). Hippo Fat provided estimates of VAT and SAT that were highly correlated with estimates using slice-O-matic (R (2)>0.9). Average VAT was 9.4% lower and average SAT was 3.7% higher using Hippo Fat compared to slice-O-matic; the overestimation of SAT tended to be greater among individuals with greater adiposity. Individual-level differences for VAT were also substantial; Hippo Fattrade mark gave estimates of VAT ranging from 1184 cm(3) less to 566 cm(3) more than estimates for the same person using slice-O-matic. Hippo Fat provides a rapid method of quantifying total VAT, although the method does not provide estimates that are interchangeable with slice-O-matic at either the group (mean) or individual level.
    International Journal of Obesity 02/2007; 31(2):285-91. · 5.22 Impact Factor
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    ABSTRACT: Although lipid profiles tend to worsen with age, it is not fully known if such age-related changes are influenced primarily by body composition and lifestyle or by other aspects of aging. We investigated the extent to which the fat and fat-free components of body mass index (BMI) and lifestyle factors influence patterns of change in lipids independent of age. Serial data were analyzed using sex-specific longitudinal models. These models use serial data from individuals to assume a general pattern of change over time, while allowing baseline age and the rate of change to vary among individuals. Serial data were obtained from 940 examinations of 269 healthy white participants (126 men, 143 women), aged 40-60 years, in the Fels Longitudinal Study. Measurements included age, the fat (FMI) and fat-free mass (FFMI) components of BMI, high-density lipoprotein (HDL-C), low-density lipoprotein (LDL-C), triglycerides (TG), total cholesterol (TC), fasting glucose and insulin, physical activity, alcohol use and smoking, and women's menopausal status and estrogen use. In both sexes, increased FMI was significantly associated with increased LDL-C, TG and TC, and decreased HDL-C. Increased FFMI was significantly related to decreased HDL-C and increased TG. Independent age effects remained significant only for LDL-C and TC in men and TC in women. Increased insulin was significantly related to increased TG in women. Moderate alcohol consumption was associated with higher HDL-C in men. Physical activity lowered male LDL-C and TC levels, and increased female HDL-C levels. Menopause was associated with increases in LDL-C. Premenopausal women not using estrogen had significantly lower HDL-C, TG, and TC than postmenopausal women taking estrogen. (1) Age is an important independent predictor for LDL-C and TC in men, and TC in women, but it is not as influential as body composition and lifestyle on HDL-C and TG in men and women, and LDL-C in women. (2) Increasing FMI is the major contributor to elevated TC, LDL-C and TG levels, and decreased HDL-C levels in men and women. (3) FFMI significantly influences HDL and TG levels in both sexes. (4) Maintaining a lower BMI via a reduced fat component may be more beneficial in lowering CVD risks than other factors.
    International Journal of Obesity 03/2006; 30(2):251-60. · 5.22 Impact Factor
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    ABSTRACT: The purpose of this study was to evaluate the influence of menarcheal age on changes in insulin, glucose, lipids, and blood pressure during adolescence and to assess whether body composition modifies this relationship. We examined 391 girls, a subset of Fels Longitudinal Study female participants (8-21 yr of age). Self-reported menarcheal age was classified based on the National Health and Nutrition Examination Survey III distribution, in which early menarche was at the 25th percentile or less (11.9 yr). Age at menarche was examined in relation to measures of body composition [e.g. fat-free mass (FFM) and percent body fat (PBF)], insulin resistance, blood pressure, and lipid profile. The effects of menarcheal age and body composition on cardiovascular disease risk factor changes were analyzed with serial data mixed models. Median menarcheal age was 12.7 yr (range, 9.8-17.0 yr), with 91 girls (23%) classified as early menarche. Girls with early menarche had more deleterious changes in insulin, glucose, blood pressure, FFM, and PBF levels than girls with average or late menarche. Menarcheal age adversely affected cardiovascular disease risk factor changes independent of age and changes in FFM or PBF. Girls with early menarche exhibited elevated blood pressure and glucose intolerance compared with later maturing girls, independent of body composition.
    Journal of Clinical Endocrinology &amp Metabolism 06/2005; 90(5):2718-24. · 6.43 Impact Factor
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    ABSTRACT: A decline in the age at menarche was recently reported for US girls. Although it is possible that this recent drop stems from the concurrent increase in childhood obesity, few longitudinal studies of growth and development have been undertaken to specifically address the temporal relation between growth, adiposity, and the age at menarche. The objective was to simultaneously examine the effects of birth cohort (secular trend) and rate of maturation (age at menarche) on the timing and pattern of increases in body mass index (BMI) during adolescence in girls. We applied mixed-effects polynomial models to serial BMI data, spanning from 6 y before menarche to 6 y after menarche, obtained from 211 girls enrolled in the Fels Longitudinal Study. We examined the effects of birth cohort (defined as girls born 1929-1946, 1947-1964, and 1965-1983) and age at menarche (defined as < or =11.9 y, 12.0-13.1 y, and > or =13.2 y) on the magnitude and velocity of BMI during adolescence. BMI and BMI velocity in girls born after 1965 were significantly greater than those of girls of earlier birth cohorts, despite stability in the mean age at menarche. Although girls with early menarche tended to have significantly higher BMIs than did girls with average or later menarche, these differences did not emerge until after menarche. These data suggest that increases in relative weight are a consequence, rather than a determinant, of the age at menarche and that secular changes in BMI and in the mean age at menarche could be independent phenomena.
    American Journal of Clinical Nutrition 08/2004; 80(2):441-6. · 6.50 Impact Factor
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    ABSTRACT: A number of recent reports suggest that the average age at menarche of US girls has declined over the past 20 years. Because the putative declines in the age at menarche are concurrent with increases in childhood body mass index (BMI), it has been suggested that these two trends may be causally linked. We examined differences in mean age of menarche in Fels Longitudinal Study girls who were born in six 10-year birth cohorts (1930s, 1940s, 1950s, 1960s, 1970s, and 1980s) and simultaneous cohort changes in mean BMI measured cross-sectionally at selected ages from 3-35 years (n = 371). Girls born in the 1980s had a mean age at menarche of 12.34 years, which was approximately 3-6 months earlier than that of girls born previously (P < 0.001). While the mean BMI values at ages 25 and 35 generally increased from the 1930s to the 1970s, the mean BMI during childhood and adolescence remained constant across the six birth cohorts. In summary, we found no evidence that the recent decline in the age at menarche in the Fels Longitudinal Study girls was reflected in concurrent increases in BMI at any point in childhood or adolescence. Conversely, girls born in the 1960s and 1970s have subsequently become heavier in young and mid-adulthood than were girls from earlier birth cohorts, without any concurrent change in the mean age at menarche over that time period. These two findings suggest that population-level shifts in BMI and the timing of menarche are largely independent, although sometimes coincident, processes.
    American Journal of Human Biology 07/2004; 16(4):453-7. · 2.34 Impact Factor
  • Karen E Remsberg, Roger M Siervogel
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    ABSTRACT: As the leading cause of chronic disease mortality in developed nations, cardiovascular disease is a widely prevalent condition that is integral to evaluation of aging populations. Chronic diseases such as coronary heart disease, hypertension and type 2 diabetes have been associated with adulthood body composition-namely excess body fat, altered lipid levels and elevated blood pressures. The Fels Longitudinal Study conducted at the Lifespan Health Research Center at Wright State University's School of Medicine has examined these same health status indicators-body composition, blood pressure, lipids, maturation, and hormones-during early life and their relationships to developing risk factors for these chronic diseases in adulthood. Research conducted during the past 10 years has shown health status indicators to track over time from childhood to adulthood. Furthermore, chronic disease risk factors attained during childhood, adolescence or early adulthood may represent an early warning system for future risk of developing cardiovascular disease.
    Mechanisms of Ageing and Development 04/2003; 124(3):249-57. · 3.26 Impact Factor
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    ABSTRACT: Body composition during puberty is a marker of metabolic changes that occur during this period of growth and maturation, and, thus, holds key information regarding current and future health. During puberty, the main components of body composition (total body fat, lean body mass, bone mineral content) all increase, but considerable sexual dimorphism exists. Methods for measuring body composition (e.g. densitometry and dual-energy X-ray absorptiometry) and degree of maturity will be discussed in this review. Components of body composition show age-to-age correlations (i.e. 'tracking'), especially from adolescence onwards. Furthermore, adipose tissue is endocrinologically active and is centrally involved in the interaction between adipocytokines, insulin and sex-steroid hormones, and thus influences cardiovascular and metabolic disease processes. In conclusion, pubertal body composition is important, not only for the assessment of contemporaneous nutritional status, but also for being linked directly to the possible onset of chronic disease later in life and is, therefore, useful for disease risk assessment and intervention early in life.
    Hormone Research 02/2003; 60(Suppl 1):36-45. · 2.48 Impact Factor
  • K.E. Remsberg, E.O. Talbott, J.V. Zborowski
    Fertility and Sterility 01/2003; 80(4). · 4.17 Impact Factor
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    ABSTRACT: To evaluate the relationships between leptin, body composition, insulin resistance, androgens, and reproductive indices among women with polycystic ovary syndrome (PCOS). Matched case-control study. Academic reproductive endocrine practice; school of public health. Forty-six Caucasian women with PCOS and 46 population-based controls matched by age and body mass index (BMI). None. Leptin, insulin, androgenic hormones, body composition parameters; reproductive parameters. Overall, leptin levels among women with PCOS did not differ significantly from those of control women (20.4 +/- 14.9 vs. 21.9 +/- 14.3 ng/mL). However, within the lowest BMI tertile, women with PCOS had significantly lower leptin levels (9.6 vs. 18.3 ng/mL), comparable insulin, and higher testosterone concentrations than controls of similar body mass. Within the overweight and obese subgroups, both insulin and testosterone levels were increased among women with PCOS; leptin levels, although higher among obese cases, were not statistically different than those in controls. Below a certain BMI, hyperandrogenic women with PCOS have lower leptin levels than controls. Conversely, overweight and obese PCOS subjects appear to produce insufficient leptin for a given fat mass, relative to the degree of hyperinsulinemia, potentially because of the competing effects of adipocyte insulin resistance and androgens on leptin.
    Fertility and Sterility 10/2002; 78(3):479-86. · 4.17 Impact Factor
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    ABSTRACT: Polycystic ovary syndrome (PCOS) is a common reproductive endocrine disorder characterized by obesity, hyperandrogenism, and insulin resistance. An adverse lipid profile has also been observed in PCOS-affected women, suggesting that these individuals may be at increased risk for coronary heart disease at a young age. The objective of the present study was to evaluate subclinical atherosclerosis among women with PCOS and age-matched control subjects. A total of 125 white PCOS cases and 142 controls, aged >/=30 years were recruited. Collection of baseline sociodemographic data, reproductive hormone levels, and cardiovascular risk factors was conducted from 1992 to 1994. During follow-up (1996 to 1999), these women underwent B-mode ultrasonography of the carotid arteries for the evaluation of carotid intima-media wall thickness (IMT) and the prevalence of plaque. A significant difference was observed in the distribution of carotid plaque among PCOS cases compared with controls: 7.2% (9 of 125) of PCOS cases had a plaque index of >/=3 compared with 0.7% (1 of 142) of similarly aged controls (P=0.05). Overall and in the group aged 30 to 44 years, no difference was noted in mean carotid IMT between PCOS cases and controls. Among women aged >/=45 years, PCOS cases had significantly greater mean IMT than did control women (0.78+/-0.03 versus 0.70+/-0.01 mm, P:=0. 005). This difference remained significant after adjustment for age and BMI (P:<0.05). These results suggest that (1) lifelong exposure to an adverse cardiovascular risk profile in women with PCOS may lead to premature atherosclerosis, and (2) the PCOS-IMT association is explained in part by weight and fat distribution and associated risk factors. There may be an independent effect of PCOS unexplained by the above variables that is related to the hormonal dysregulation of this condition.
    Arteriosclerosis Thrombosis and Vascular Biology 11/2000; 20(11):2414-21. · 6.34 Impact Factor