Journal articles on the topic 'BMI change'
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Jago, Russell, Kimberly L. Drews, Robert G. McMurray, Tom Baranowski, Pietro Galassetti, Gary D. Foster, Ester Moe, and John B. Buse. "BMI Change, Fitness Change and Cardiometabolic Risk Factors Among 8th Grade Youth." Pediatric Exercise Science 25, no. 1 (February 2013): 52–68. http://dx.doi.org/10.1123/pes.25.1.52.
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This paper examined whether a two-year change in fitness, body mass index (BMI) or the additive effect of change in fitness and BMI were associated with change in cardiometabolic risk factors among youth. Cardiometabolic risk factors, BMI group (normal weight, overweight or obese) were obtained from participants at the start of 6th grade and end of 8th grade. Shuttle run laps were assessed and categorized in quintiles at both time points. Regression models were used to examine whether changes in obesity, fitness or the additive effect of change in BMI and fitness were associated with change in risk factors. There was strong evidence (p < .001) that change in BMI was associated with change in cardiometabolic risk factors. There was weaker evidence of a fitness effect, with some evidence that change in fitness was associated with change in total cholesterol, HDL-C, LDL-C and clustered risk score among boys, as well as HDL-C among girls. Male HDL-C was the only model for which there was some evidence of a BMI, fitness and additive BMI*fitness effect. Changing body mass is central to the reduction of youth cardiometabolic risk. Fitness effects were negligible once change in body mass had been taken into account.
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Douglas, Joy, Kristi Crowe-White, Amy Ellis, Chuong Bui, Saroja Voruganti, and Kristine Yaffe. "Change in Body Mass Index is Associated with Change in Cognition in Older Adults." Innovation in Aging 4, Supplement_1 (December 1, 2020): 876–77. http://dx.doi.org/10.1093/geroni/igaa057.3239.
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Abstract Background: Alzheimer’s disease and related dementias affect one in ten Americans age 65y and older. Considering the rapid growth of the aging population, identifying modifiable risk factors for cognitive decline is a public health priority. Although weight change later in life is common, its impact on cognition is unclear. The objective of this study was to examine the relationship between change in body mass index (BMI) and cognition among older adults. Methods: The Health, Aging, and Body Composition Study was a prospective study of community-dwelling adults ages 70-79y at baseline (n=3,075; 49% males, 42% African-American). Using baseline and year 10 visit data, we evaluated change in BMI and change in cognition measured by the Modified Mini-Mental Status Exam (3MS) using a linear mixed model. Change in 3MS scores were regressed on changes in time-varying BMI after controlling for blood pressure, glucose, cholesterol, race, education, biological sex, and APOE genotype. Results: At baseline, average BMI was 27.4 (n=3075) and average 3MS was 90.1 (n=3061). At year 10, average BMI was 27.1 (n=1600) and average 3MS was 88.6 (n=1598). Higher BMI was associated with less cognitive decline (ceteris paribus). This finding suggests that weight gain is associated with cognitive maintenance. The effect of an increase in BMI was largest for those underweight at baseline. Conclusion: Among underweight older adults, an increase in BMI may be desirable for maintaining cognition. Although more research is needed, these findings suggest the need for interventions to prevent unintentional weight loss among older adults.
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Byiringiro, Samuel, Binu Koirala, Tiwaloluwa Ajibewa, Eric K. Broni, Xiaoyue Liu, Khadijat Adeleye, Ruth-Alma N. Turkson-Ocran, et al. "Migration-Related Weight Changes among African Immigrants in the United States." International Journal of Environmental Research and Public Health 19, no. 23 (November 23, 2022): 15501. http://dx.doi.org/10.3390/ijerph192315501.
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(1) Background: people who migrate from low-to high-income countries are at an increased risk of weight gain, and excess weight is a risk factor for cardiovascular disease. Few studies have quantified the changes in body mass index (BMI) pre- and post-migration among African immigrants. We assessed changes in BMI pre- and post-migration from Africa to the United States (US) and its associated risk factors. (2) Methods: we performed a cross-sectional analysis of the African Immigrant Health Study, which included African immigrants in the Baltimore-Washington District of the Columbia metropolitan area. BMI category change was the outcome of interest, categorized as healthy BMI change or maintenance, unhealthy BMI maintenance, and unhealthy BMI change. We explored the following potential factors of BMI change: sex, age at migration, percentage of life in the US, perceived stress, and reasons for migration. We performed multinomial logistic regression adjusting for employment, education, income, and marital status. (3) Results: we included 300 participants with a mean (±SD) current age of 47 (±11.4) years, and 56% were female. Overall, 14% of the participants had a healthy BMI change or maintenance, 22% had an unhealthy BMI maintenance, and 64% had an unhealthy BMI change. Each year of age at immigration was associated with a 7% higher relative risk of maintaining an unhealthy BMI (relative risk ratio [RRR]: 1.07; 95% CI 1.01, 1.14), and compared to men, females had two times the relative risk of unhealthy BMI maintenance (RRR: 2.67; 95% CI 1.02, 7.02). Spending 25% or more of life in the US was associated with a 3-fold higher risk of unhealthy BMI change (RRR: 2.78; 95% CI 1.1, 6.97). (4) Conclusions: the age at immigration, the reason for migration, and length of residence in the US could inform health promotion interventions that are targeted at preventing unhealthy weight gain among African immigrants.
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Park, Susan, Sunmi Pi, Jinseub Hwang, Jae-Heon Kang, and Jin-Won Kwon. "Effects of Initial Body Mass Index and Weight Change on All-Cause Mortality: A 10-Year Cohort Study in Korea." Asia Pacific Journal of Public Health 30, no. 3 (February 18, 2018): 217–26. http://dx.doi.org/10.1177/1010539518756981.
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We evaluated the effects of baseline body mass index (BMI) and its changes over 4 years on all-cause mortality in Korean population. We analyzed 351 735 participants whose BMI was measured in both 2002/2003 and 2006/2007. Mortality was assessed until 2013. Multivariate hazard ratios for all-cause mortality were estimated. Underweight and severe obesity with BMI >30 kg/m2 were significantly associated with higher mortality. Similarly, >5% decrease or >10% increase of BMI for 4 years was associated with the increased risk of death. Comparing the results between baseline BMI and BMI change, the BMI change showed more stable associations with mortality than the baseline BMI in subgroup analysis such as nonsmokers and healthy participants. This study suggests that BMI change could be a useful health indicator along with obesity level by BMI. In addition, maintaining a healthy weight is needed for longevity, but rapid weight change should be carefully monitored.
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Muriyati, Muriyati, Patima Patima, and A. Suswani. "AEROBIC EXERCISE ON BODY MASS INDEX (BMI) CHANGE IN PERSON WITH OVERWEIGHT AND OBESITY." INDONESIAN NURSING JOURNAL OF EDUCATION AND CLINIC (INJEC) 2, no. 1 (March 13, 2018): 32. http://dx.doi.org/10.24990/injec.v2i1.5.
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Introduction. Aerobic Gymnastics is one type of exercise that increases fatty acid oxidation so that can lose weight. The purpose of this study was to determine the effect of aerobic exercise on body mass index (BMI) changes in person with obesity. Methods. This study was a quasi-experimental study using a pre-post test design. Individuals with obesity / overweight do aerobic exercise for 3 times a week for 6 weeks. Before aerobic exercise, the body mass index (BMI) measured and then after aerobic exercise done reassess the Body Mass Index (BMI). The number of sample studied were 30 women aged between 17-22 years old.Results.The results showed that BMI scores before aerobic exercise intervention is average of 27.54 and the average BMI of the respondents after attending aerobics for 6 weeks was 26.65 with a probability value (p = 0.000) smaller than (p = 0.05), which means that there is effect of aerobic exercise with BMI change. Discussion. BMI levels have changed significantly after aerobic exercise for 6 weeks.Keywords: BMI, aerobic, obesity
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Brismar, T. B., and H. Ringertz. "Effect of Bone Density of the Head on Total Body Dexa Measurements in 100 Healthy Swedish Women." Acta Radiologica 37, no. 1P1 (January 1996): 101–6. http://dx.doi.org/10.1177/02841851960371p120.
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Purpose: The aims of this study were to examine the bone areal density of the head and how it varied in relation to the density of the rest of the skeleton, and with age, and body mass index (BMI). Our intention was to study the feasibility of excluding the head from the rest of the body, a method which might improve the fracture prediction power of bone mineral measurements. Material and Methods: Bone mineral per area (BMA) and bone mineral content (BMC) (g) were determined in 100 consecutive female volunteers, aged 17 to 78 years, with total and partial body measurements. Results: BMC of the head was found to be 20.2±2.2% of that for the total body. The BMA of the head was 2.38±0.21 times higher than that of the rest of the body. The correlation between the BMA of the head and the rest of the body was significant (r=0.73). The average change in z-score (referred to the same age group in our material) was 0.20 when the head was excluded from total body BMA. The BMA of a) total body, b) total body, head excluded, and c) head decreased with age. The BMA of the head was correlated to BMI in the older age groups (p<0.01). The relative statistical uncertainty for repeated measurement of head BMA was 1.8%. Conclusion: The change of the bone density of the head with age and BMI, in comparison to that of the rest of the skeleton, suggests that when the head is excluded from total body BMA better predictive value for fracture risk is obtained.
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Kim, So Young, Dae Myoung Yoo, Soo-Hwan Byun, Chanyang Min, Ji Hee Kim, Mi Jung Kwon, Joo-Hee Kim, and Hyo Geun Choi. "Association between Temporomandibular Joint Disorder and Weight Changes: A Longitudinal Follow-Up Study Using a National Health Screening Cohort." International Journal of Environmental Research and Public Health 18, no. 22 (November 10, 2021): 11793. http://dx.doi.org/10.3390/ijerph182211793.
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This study aimed to investigate BMI changes following a temporomandibular joint disorder (TMJD) diagnosis. The Korean National Health Insurance Service-Health Screening Cohort from 2002 to 2015 was used. In Study I, 1808 patients with TMJD (TMJD I) were matched with 7232 participants in comparison group I. The change in BMI was compared between the TMJD I and comparison I groups for 1 year. In study II, 1621 patients with TMJD (TMJD II) were matched with 6484 participants in comparison group II participants. The change in BMI was compared between the TMJD II and comparison II groups for 2 years. In Study I, the BMI change was not associated with TMJD. In Study II, the BMI change was associated with TMJD in the interaction of the linear mixed model (p = 0.003). The estimated value (EV) of the linear mixed model was −0.082. The interaction was significant in women < 60 years old, women ≥ 60 years old, and the obese I category. TMJD was not associated with BMI changes after 1–2 years in the overall population. In women and obese patients, TMJD was associated with a decrease in BMI after 2 years.
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Bygdell, Maria, Claes Ohlsson, and Jenny M. Kindblom. "A secular trend of increasing pubertal BMI change among Swedish adolescents." International Journal of Obesity 46, no. 2 (November 6, 2021): 444–46. http://dx.doi.org/10.1038/s41366-021-01011-0.
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AbstractPubertal BMI change is an independent risk marker of cardiovascular mortality/morbidity. Previous studies demonstrated a secular trend of increased childhood BMI but it is unknown if there is a concomitant secular trend regarding pubertal BMI change. The aim of this study was to describe the trend in pubertal BMI change. We collected heights and weights before and after puberty from school health records and military conscript records for boys born every five years during 1946–1991 (n = 3650, total cohort) and calculated pubertal BMI change (young adult BMI at 20 years of age minus childhood BMI at 8 years of age) for all study participants. A secular trend of increasing pubertal BMI change during the study period was observed. The increase in pubertal BMI change (0.27 kg/m2 per decade [0.22; 0.32]) explained 54% of the secular trend of increasing young adult BMI (0.50 kg/m2 per decade [0.43; 0.57]). We made the novel observation that there is a secular trend of increasing pubertal BMI change. We propose that the secular trend of increasing pubertal BMI change might contribute more than the secular trend of increasing childhood BMI to the adverse cardiovascular health consequences associated with the ongoing obesity epidemic.
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BARANOWSKI, TOM, TZU-AN CHEN, JASON A. MENDOZA, TERESIA O’CONNOR, JANICE BARANOWSKI, and RUSSELL JAGO. "Prospective BMI Category Change Associated with Cardiovascular Fitness Change." Medicine & Science in Sports & Exercise 45, no. 2 (February 2013): 294–98. http://dx.doi.org/10.1249/mss.0b013e3182703774.
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White, Michelle J., Jessica Hoffman, Sarah Armstrong, and Asheley C. Skinner. "Body Mass Index Change Between Referral to and Enrollment in Pediatric Weight Management." Clinical Pediatrics 59, no. 1 (October 28, 2019): 70–74. http://dx.doi.org/10.1177/0009922819884587.
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This study describes changes in body mass index z score (BMI z) and percent of 95th percentile (P95) between referral to pediatric weight management (PWM) and initial PWM visit. We conducted a prospective cohort analysis among subjects (n = 77) aged 5 to 11 years referred to PWM and compared height and weight at time of referral versus initial PWM visit. Mean BMI z decreased by 0.05, and P95 decreased by 1.48 across all age groups (both P < .01) from time of referral to initial visit. Children 5 to 8 years old experienced a greater BMI z change than older children (−0.07 vs −0.02; P < .05). Interval BMI z change was greater for non-Hispanic White and Hispanic children compared with non-Hispanic Blacks (−0.10 vs −0.01; P < .001). There were no subgroup differences in P95. Interval BMI changes between referral and treatment approach half the effect reported by some PWM programs. Referral to PWM may motivate pretreatment lifestyle changes in some patients.
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Kadey, Kylie R., John L. Woodard, Allison C. Moll, Kristy A. Nielson, J. Carson Smith, Sally Durgerian, and Stephen M. Rao. "Five-Year Change in Body Mass Index Predicts Conversion to Mild Cognitive Impairment or Dementia Only in APOE ɛ4 Allele Carriers." Journal of Alzheimer's Disease 81, no. 1 (May 4, 2021): 189–99. http://dx.doi.org/10.3233/jad-201360.
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Background: Body mass index (BMI) has been identified as an important modifiable lifestyle risk factor for dementia, but less is known about how BMI might interact with Apolipoprotein E ɛ4 (APOE ɛ4) carrier status to predict conversion to mild cognitive impairment (MCI) and dementia. Objective: The aim of this study was to investigate the interaction between APOE ɛ4 status and baseline (bBMI) and five-year BMI change (ΔBMI) on conversion to MCI or dementia in initially cognitively healthy older adults. Methods: The associations between bBMI, ΔBMI, APOE ɛ4 status, and conversion to MCI or dementia were investigated among 1,289 cognitively healthy elders from the National Alzheimer’s Coordinating Center (NACC) database. Results: After five years, significantly more carriers (30.6%) converted to MCI or dementia than noncarriers (17.6%), p < 0.001, OR = 2.06. Neither bBMI (OR = 0.99, 95%CI = 0.96–1.02) nor the bBMI by APOE interaction (OR = 1.02, 95%CI = 0.96–1.08) predicted conversion. Although ΔBMI also did not significantly predict conversion (OR = 0.90, 95%CI = 0.78–1.04), the interaction between ΔBMI and carrier status was significant (OR = 0.72, 95%CI = 0.53–0.98). For carriers only, each one-unit decline in BMI over five years was associated with a 27%increase in the odds of conversion (OR = 0.73, 95%CI = 0.57–0.94). Conclusion: A decline in BMI over five years, but not bBMI, was strongly associated with conversion to MCI or dementia only for APOE ɛ4 carriers. Interventions and behaviors aimed at maintaining body mass may be important for long term cognitive health in older adults at genetic risk for AD.
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Drozek, David, Alexandria DeFabio, Randi Amstadt, and Godwin Y. Dogbey. "Body Mass Index Change as a Predictor of Biometric Changes following an Intensive Lifestyle Modification Program." Advances in Preventive Medicine 2019 (March 24, 2019): 1–5. http://dx.doi.org/10.1155/2019/8580632.
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The initial benefits of lifestyle modification programs such as reduction in chronic and cardiovascular diseases (CVD) risk factors have been well documented. However, such positive effects may deteriorate over time following relapse into inactivity. Timely detection of weight regain leading to the deterioration of the accrued benefits could trigger early resumption of intensive lifestyle intervention. To date, no known cost-effective, noninvasive approach for monitoring long-term outcomes has yet been established. The purpose of this study was to determine if body mass index (BMI) change predicted changes in other CVD biometric markers during an intensive lifestyle modification program. This study was an observational, retrospective review of records of participants from the Complete Health Improvement Program (CHIP). Biomarker changes of participants in this community-based Intensive Therapeutic Lifestyle Modification Program (ITLMP) offered in Athens, Ohio, a rural Appalachian college town, between April 2011 and June 2017 were reviewed retrospectively. BMI, heart rate (Pulse), systolic blood pressure (SBP), diastolic blood pressure (DBP), and fasting blood levels of total cholesterol (TC), low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides (TG), and glucose (FBS) were monitored before and after program completion. Data were analyzed using a multivariate general linear model. The sample analyzed consisted of 620 participants (mean age of 52.3±13.0 years, 74.5% female). Controlling for age and gender, BMI change significantly predicted 5 out of the 8 biomarker changes measured [Wilk’s λ = 0.939, F(8,526) = 4.29, p <.0001]. Specifically, a 1-point BMI decrease was associated with 4.4 units decrease in TC, 3.2 units in LDL, 5.3 units in TG, 2 units in SBP, and 1 unit in DBP (all p values < .05). These results suggest that change in BMI may be a useful predictor of change in other CVD biomarkers’ outcomes during and after an ITLMP participation. Tracking BMI, therefore, could serve as a proxy measure for identifying regressing biomarker changes following participation in an ITLMP leading to a timelier reassessment and intervention. Future studies evaluating the value of BMI as a surrogate for highlighting overall cardiovascular health are warranted.
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Fukuma, Shingo, Tatsuyoshi Ikenoue, Jennifer Bragg-Gresham, Edward Norton, Yukari Yamada, Daichi Kohmoto, and Rajiv Saran. "Body mass index change and estimated glomerular filtration rate decline in a middle-aged population: health check-based cohort in Japan." BMJ Open 10, no. 9 (September 2020): e037247. http://dx.doi.org/10.1136/bmjopen-2020-037247.
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BackgroundObesity is a growing public health problem worldwide. We evaluated the mediators and association between changes in obesity metrics and renal outcomes in the general population.MethodsUsing the Japanese nationwide health check-based cohort from April 2011 to March 2019, we selected individuals aged 40–74 years, with a baseline estimated glomerular filtration rate (eGFR) ≥45 mL/min/1.73 m2, whose body mass index (BMI) change was assessed. The primary outcome was combined 30% decline in eGFR, eGFR <15 mL/min/1.73 m2 and end-stage renal disease.ResultsDuring 245 147 person-years’ follow-up among 50 604 participants (mean eGFR, 83.7 mL/min/1.73 m2; mean BMI, 24.1 kg/m2), 645 demonstrated eGFR decline (incidence rate 2.6/1000 person-years, 95% CI: 2.4 to 2.8). We observed continued initial changes in BMI for over 6 years and a U-shaped association between BMI change and eGFR decline. Compared with 0% change in BMI, adjusted HRs for changes of −10%, −4%, 4% and 10% were 1.53 (95% CI: 1.15 to 2.04), 1.14 (95% CI: 1.01 to 1.30), 1.16 (95% CI: 1.02 to 1.32) and 1.87 (95% CI: 1.25 to 2.80), respectively. The percentage of excess risk of BMI increase (>4%) mediated by three risk factors (blood pressure, haemoglobin A1c and total cholesterol), was 13.3%.ConclusionIn the middle-aged Japanese population, both, increase and decrease in BMI were associated with subsequent eGFR decline. Changes in risk factors mediated a small proportion of the association between BMI increase and eGFR decline. Our findings support the clinical significance of monitoring BMI as a renal risk factor.
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Kronschnabl, Judith M., Thorsten Kneip, Luzia M. Weiss, and Michael Bergmann. "Bodyweight change and cognitive performance in the older population." PLOS ONE 16, no. 4 (April 21, 2021): e0249651. http://dx.doi.org/10.1371/journal.pone.0249651.
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Preservation of cognitive function is one of the major concerns in contemporary ageing societies. At the same time, overweight and obesity, which have been identified as risk factors for poor health development, have been increasing in many countries all over the world. This study examines the relationship between bodyweight change and cognitive decline in old age and it aims to determine whether and how changes in body mass index (BMI) affect the development of cognitive functioning in old age. Using longitudinal data from the Survey of Health, Ageing and Retirement in Europe (SHARE), covering four waves between 2006 and 2016 with 58,389 participants from 15 countries aged 50+, we estimated asymmetric fixed effects models by gender, adding possible confounding variables such as age, grip strength, health conditions, and physical activity. Additionally, we investigated possible heterogeneity in the BMI-cognition relation. We found a positive association between BMI change and change in cognitive performance, which was dominantly driven by BMI decrease. Weight loss was typically negatively related to cognition, particularly at low levels of BMI and mainly due to health conditions affecting both bodyweight and cognitive performance. Weight gain was, on average, not significantly related to cognitive performance; only respondents with preceding weight loss profited from small increases in BMI. Our analyses provide no support for an “obesity paradox” in cognition, according to which higher weight preserves cognition in old age. The association between weight change and cognitive performance in older age is based on weight changes being related to illness and recovery.
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Naess, Marit, Erik R. Sund, Turid Lingaas Holmen, and Kirsti Kvaløy. "Implications of parental lifestyle changes and education level on adolescent offspring weight: a population based cohort study - The HUNT Study, Norway." BMJ Open 8, no. 8 (August 2018): e023406. http://dx.doi.org/10.1136/bmjopen-2018-023406.
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ObjectiveObesity tends to cluster in families reflecting both common genetics and shared lifestyle patterns within the family environment. The aim of this study was to examine whether parental lifestyle changes over time, exemplified by changes in weight and physical activity, could affect offspring weight in adolescents and if parental education level influenced the relationship.Design, setting and participantsThe population-based cohort study included 4424 parent-offspring participants from the Nord-Trøndelag Health Study, Norway. Exposition was parental change in weight and physical activity over 11 years, and outcome was offspring weight measured in z-scores of body mass index (BMI) in mixed linear models.ResultsMaternal weight reduction by 2–6 kg was significantly associated with lower offspring BMI z-scores: −0.132 (95% CI −0.259 to −0.004) in the model adjusted for education. Parental weight change displayed similar effect patterns on offspring weight regardless of parents’ education level. Further, BMI was consistently lower in families of high education compared with low education in the fully adjusted models. In mothers, reduced physical activity level over time was associated with higher BMI z-scores in offspring: 0.159 (95% CI 0.030 to 0.288). Associations between physical activity change and adolescent BMI was not moderated by parental education levels.ConclusionLifestyle changes in mothers were associated with offspring BMI; reduced weight with lower—and reduced physical activity with higher BMI. Father’s lifestyle changes, however, did not significantly affect adolescent offspring’s weight. Overall, patterns of association between parental changes and offspring’s BMI were independent of parental education levels, though adolescents with parents with high education had lower weight in general.
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Feng, Tingting, Malmo Vegard, Linn B. Strand, Lars E. Laugsand, Bjørn Mørkedal, Dagfinn Aune, Lars Vatten, et al. "Weight and weight change and risk of atrial fibrillation: the HUNT study." European Heart Journal 40, no. 34 (June 17, 2019): 2859–66. http://dx.doi.org/10.1093/eurheartj/ehz390.
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Abstract Aims Although obesity has been associated with risk of atrial fibrillation (AF), the associations of long-term obesity, recent obesity, and weight change with AF risk throughout adulthood are uncertain. Methods and results An ambispective cohort study was conducted which included 15 214 individuals. The cohort was created from 2006 to 2008 (the baseline) and was followed for incident AF until 2015. Weight and height were directly measured at baseline. Data on previous weight and height were retrieved retrospectively from measurements conducted 10, 20, and 40 years prior to baseline. Average body mass index (BMI) over time and weight change was calculated. During follow-up, 1149 participants developed AF. The multivariable-adjusted hazard ratios were 1.2 (95% confidence interval 1.0–1.4) for average BMI 25.0–29.9 kg/m2 and 1.6 (1.2–2.0) for average BMI ≥30 kg/m2 when compared with normal weight. The association of average BMI with AF risk was only slightly attenuated after adjustment for most recent BMI. In contrast, current BMI was not strongly associated with the risk of AF after adjustment for average BMI earlier in life. Compared with stable BMI, both loss and gain in BMI were associated with increased AF risk. After adjustment for most recent BMI, the association of BMI gain with AF risk was largely unchanged, while the association of BMI loss with AF risk was weakened. Conclusion Long-term obesity and BMI change are associated with AF risk. Obesity earlier in life and weight gain over time exert cumulative effects on AF development even after accounting for most recent BMI.
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Chow, Lydia D., Elisa M. Ledet, Allie E. Steinberger, Jeffrey R. Guccione, and A. Oliver Sartor. "Body mass index at mCRPC, weight change, and survival in advanced prostate cancer." Journal of Clinical Oncology 34, no. 2_suppl (January 10, 2016): 270. http://dx.doi.org/10.1200/jco.2016.34.2_suppl.270.
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270 Background: Body mass index (BMI) at diagnosis is associated with increased risk of fatal prostate cancer, but the link between BMI at mCRPC and cancer progression is less clear. Cachexia, often defined as involuntary weight loss > 5% over 6 months, is common in advanced cancers. The goal of this study was to examine the link between BMI at mCRPC and weight change as it relates to cancer progression, the outcomes of survival, and treatment use in a single-institution setting. Methods: 58 mCRPC patients treated at Tulane Hospital were identified, 41 of whom had an overweight BMI at mCRPC (BMI > 25) and 17 with normal BMI at mCRPC (BMI < 25). All patients had a confirmed prostate cancer death. Survival, treatment history, and percent weight change were compared according to BMI status. Rate of percent weight change was defined as the change in weight per day, from date of mCRPC diagnosis to the last treatment stop date or death date (“mCRPC days”). Linear regression, overall survival (OS), and nonparametric analyses were performed. Results: There was no significant difference between the normal and overweight BMI groups in overall survival, from date of diagnosis to death (median = 1835 days vs. 2710 days respectively). Additionally, the difference in survival from mCRPC to death was not statistically significant (median = 630 days vs. 799 days, p = 0.115). Use of Taxotere was not significantly different (47% vs. 68% respectively); however, overweight patients (n = 28) more likely received Abiraterone than normal BMI patients (n = 2) (p-value = 0.0001). The rate of percent weight change was significantly different for normal and overweight patients (mean = –0.050%/day vs. –0.019%/day, p = 0.003). Linear regression analysis showed that mCRPC days had a significant effect on percent weight change (p = 0.0109), and this effect was not significantly different between BMI groups (p = 0.6991). Conclusions: Survival after mCRPC was not significantly different between BMI groups. We observed a significant effect of mCRPC days on percent weight change, with a similar effect for both BMI groups. This outcome is expected, as more time would allow for greater weight changes to occur. Larger studies are needed to fully evaluate these observations.
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Thieszen, Carmen L., Steven G. Aldana, Marita L. Mahoney, David A. Vermeersch, Ray M. Merrill, Hans A. Diehl, Roger L. Greenlaw, and Heike Englert. "The Coronary Health Improvement Project (CHIP) for Lowering Weight and Improving Psychosocial Health." Psychological Reports 109, no. 1 (August 2011): 338–52. http://dx.doi.org/10.2466/06.10.13.17.pr0.109.4.338-352.
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This study extends previous research evaluating the association between the CHIP intervention, change in body weight, and change in psychological health. A randomized controlled health intervention study lasting 4 wk. was used with 348 participants from metropolitan Rockford, Illinois; ages ranged from 24 to 81 yr. Participants were assessed at baseline, 6 wk., and 6 mo. The Beck Depression Inventory (BDI) and three selected psychosocial measures from the SF–36 Health Survey were used. Significantly greater decreases in Body Mass Index (BMI) occurred after 6 wk. and 6 mo. follow-up for the intervention group compared with the control group, with greater decreases for participants in the overweight and obese categories. Significantly greater improvements were observed in BDI scores, role-emotional and social functioning, and mental health throughout follow-up for the intervention group. The greater the decrease in BMI through 6 wk., the better the chance of improved BDI score, role-emotional score, social functioning score, and mental health score, with odds ratios of 1.3 to 1.9. Similar results occurred through 6 mo., except the mental health variable became nonsignificant. These results indicate that the CHIP intervention significantly improved psychological health for at least six months afterwards, in part through its influence on lowering BMI.
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Stackpole, Kristin, Philip Khoury, Robert Siegel, and Amanda Gier. "Body Composition versus BMI as Measures of Success in a Clinical Pediatric Weight Management Program." Reports 3, no. 4 (October 20, 2020): 32. http://dx.doi.org/10.3390/reports3040032.
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The high rates and long-term medical consequences of childhood obesity make it a public health crisis requiring effective diagnosis, treatment, and prevention. Although BMI is an adequate screening tool for obesity, monitoring BMI change is not always the best measure of success in treating patients in a pediatric weight management program. Our retrospective study evaluated the proportion of patients that achieved favorable changes in body composition by bioelectrical impedance analysis in the absence of improvements in BMI, BMI percentile, or percent of the 95th percentile for BMI. It was found that 30% of patients whose BMI increased by 1.0 kg/m2 or more, 31.6% of patients with stable or increasing BMI percentiles, and 28% with stable or increasing percent of the 95th percentile for BMI demonstrated an improvement in body composition (skeletal muscle mass and body fat percentage). Body composition is an important measure of success for a subset of patients who otherwise may believe that their efforts in lifestyle change have not been effective. Our results suggest that including body fat percentage as a measure of success in evaluating the progress of patients participating in a pediatric weight management program is appropriate and may more accurately track success than change in BMI or BMI percentile alone.
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Brannsether, Bente, Geir Egil Eide, Mathieu Roelants, Robert Bjerknes, and Pétur Benedikt Júlíusson. "BMI and BMI SDS in childhood: annual increments and conditional change." Annals of Human Biology 44, no. 1 (March 10, 2016): 28–33. http://dx.doi.org/10.3109/03014460.2016.1151933.
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McClurg, Dylan Peter, Mika Gissler, Miriam Gatt, Jacqueline Wallace, and Sohinee Bhattacharya. "Does interpregnancy BMI change affect the risk of complications in the second pregnancy? Analysis of pooled data from Aberdeen, Finland and Malta." International Journal of Obesity 46, no. 1 (October 4, 2021): 178–85. http://dx.doi.org/10.1038/s41366-021-00971-7.
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Abstract Objective Weight management interventions during pregnancy have had limited success in reducing the risk of pregnancy complications. Focus has now shifted to pre-pregnancy counselling to optimise body weight before subsequent conception. We aimed to assess the effect of interpregnancy body mass index (BMI) change on the risk of perinatal complications in the second pregnancy. Methods A cohort study was performed using pooled maternity data from Aberdeen, Finland and Malta. Women with a BMI change of ±2 kg/m2 between their first and second pregnancies were compared with those who were BMI stable (remained within ±2 kg/m2). Outcomes assessed included pre-eclampsia (PE), intrauterine growth restriction (IUGR), preterm birth, birth weight, and stillbirth in the second pregnancy. We also assessed the effect of unit change in BMI for PE and IUGR. Logistic regression was used to calculate odds ratios with 95% confidence intervals. Results An increase of ≥2 kg/m2 between the first two pregnancies increased the risk of PE (1.66 (1.49–1.86)) and high birthweight (>4000 g) (1.06 (1.03–1.10)). A reduction of ≥2 kg/m2 increased the chance of IUGR (1.15 (1.01–1.31)) and preterm birth (1.14 (1.01–1.30)), while reducing the risk of instrumental delivery (0.75 (0.68–0.85)) and high birthweight (0.93 (0.87–0.98)). Reducing BMI did not significantly decrease PE risk in women with obesity or those with previous PE. A history of PE or IUGR in the first pregnancy was the strongest predictor of recurrence independent of interpregnancy BMI change (5.75 (5.30–6.24) and (7.44 (6.71–8.25), respectively). Conclusion Changes in interpregnancy BMI have a modest impact on the risk of high birthweight, PE and IUGR in contrasting directions. However, a prior history of PE and IUGR is the dominant predictor of recurrence at second pregnancy.
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Kwon, Youngsuk, Ji Su Jang, Sung Mi Hwang, Jae Jun Lee, Seok Jun Hong, Sung Jun Hong, Byung Yong Kang, and Ho Seok Lee. "The change of endotracheal tube cuff pressure during laparoscopic surgery." Open Medicine 14, no. 1 (May 30, 2019): 431–36. http://dx.doi.org/10.1515/med-2019-0046.
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AbstractBackgroundWe evaluated the endotracheal tube cuff pressure (Pcuff) changes during pneumoperitoneum for laparoscopic cholecystectomy and the correlations between body mass index (BMI), pneumoperitoneum time, and Pcuff changes.MethodsTotal 60 patients undergoing laparoscopic cholecystectomy were allocated to either a study group (BMI ≥ 25 kg/m2) or a control group (BMI < 25 kg/m2). The endotracheal intubation was performed with a high-volume low-pressure cuffed oral endotracheal tube. A manometer was connected to the pilot balloon using a 3-way stopcock and the cuff was inflated. The change in Pcuff was defined as the difference between the pressure just before intra-abdominal CO2 insufflation and the pressure before CO2 desufflation.ResultsPcuff increased to 5.3 ± 3.6 cmH2O in the study group and 5.7 ± 5.4 cmH2O in the control group. There was no significant difference between two groups. While BMI was not correlated with change in Pcuff (r = 0.022, p = 0.867), there was a significant correlation between change in Pcuff and the duration of pneumoperitoneum (r = 0.309, p = 0.016).ConclusionThe change in Pcuff was not affected by BMI and was significantly correlated with pneumoperitoneum time. We recommend regular measurement and adjustment of Pcuff during laparoscopic surgery.
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Annesi, James J. "Exercise Program-Related Psychosocial Changes Promote Healthy Weight in Youth." Open Public Health Journal 10, no. 1 (August 10, 2017): 126–31. http://dx.doi.org/10.2174/1874944501710010126.
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Background: An inappropriately high weight in children is a predictor of health risks. Reliable interventions that are easily disseminated are needed. Objective: Based on findings with adults, exercise-support methods might be leveraged to change behavioral predictors of a healthy body composition in youth. Analyses of changes in theory-based psychological variables’ association with changes in body composition within the context of youth-tailored treatment are required. Method: A 45 minute/day, 4 day/week, social cognitive/self-efficacy theory-based after-school care protocol, Youth Fit 4 Life, was tested in children of a normal (n=54) and overweight/obese (n=32) body composition over a school year. The treatment’s emphasis was on improvements in mood, self-efficacy, and self-regulation related to physical activity. Validated self-report measures of negative mood, self-regulation, and self-efficacy, and BMI, were administered at baseline, and months 3 and 9. The prediction of BMI change from changes in the psychosocial variables was assessed using multiple regression analyses. Results: Change in BMI and improvements in the aforementioned psychosocial factors were significant over both 3 and 9 months, and did not differ between body composition groups. Analyses indicated that over 3 months, self-regulation change was a significant predictor of BMI change (β=-0.26, SE=0.05, P=0.03), while over 9 months, self-efficacy change significantly predicted BMI change (β=-0.21, SE=0.02, P=0.05). Conclusion: After replications and extensions focused also on eating behaviors, it was suggested that the inexpensive and efficient Youth Fit 4 Life protocol might be scalable across community venues to address childhood overweight and obesity.
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Suzuki, Yusuke, Hiroko Tsunoda, Takeshi Kimura, and Hideko Yamauchi. "BMI change and abdominal girth as risk factors of breast cancer." Journal of Clinical Oncology 35, no. 15_suppl (May 20, 2017): e13082-e13082. http://dx.doi.org/10.1200/jco.2017.35.15_suppl.e13082.
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e13082 Background: While obesity is considered the risk factors of breast cancer, Asian women are tends to be lower BMI compared with Western populations and there are not much reports that studied association between obesity and risk of breast cancer in Asian women. In this study, we analyzed the associations of breast cancer incidence and body mass index at age 18-20 (BMI 18-20y), BMI at research entry (BMI at entry), change of the BMI from BMI 18-20y to BMI at entry (BMI change), abdominal girth at research entry (AG), HbA1c [N] at research entry (HbA1c). Methods: We used data of the women who had undergone medical check-ups and opportunistic breast cancer screening at least twice at the Center for Preventive Medicine of St. Luke’s International Hospital between April 1, 2005 and March 31, 2014. Statistical analysis was done by using multivariate Cox proportional hazards model to investigate the hazard ratio (HR) at 95% confidence intervals (95% CI). Results: In this 10 year period, 30,109 women (20,043 women were premenopausal and 10,066 women were postmenopausal women) received opportunistic breast cancer screening at least twice. After analysis of 131656.6 person-years follow up during 10 years, 325 initial breast cancer cases were identified 202 cases in premenopausal women, and 123 cases in postmenopausal women. Among postmenopausal women, BMI change and AG were positively associated with breast cancer incidence. Women whose BMI change were major gain group (> +5.0) were significantly likely to develop breast cancer compared with stable group (BMI change were between -2.5 to +2.5) [HR: 1.902 (95% CI = 1.202-3.009)]. Large AG ( > 90cm) was significant risk to develop breast cancer versus less than 70cm [HR: 2.500 (95% CI = 1.091-5.730)]. In the analysis classified BMI18-20y more and less than 20 kg/m2, large BMI18-20y ( > 20 kg/m2) postmenopausal women with high HbA1c ( > 6.5) was more likely to develop breast cancer compared with low HbA1c ( < 5.5) [HR: 3.325(95% CI = 1.307-8.460)]. Conclusions: Increase of BMI after age of 18-20 years and large AG in postmenopausal women have positive association with breast cancer development. High HbA1c women whose BMI18-20y was over 20 kg/m2 are significantly to develop breast cancer.
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Abu-Khalaf, Maysa, Fnu Nikita, Ayako Shimada, Hannah Hackbart, Dina Alnabulsi, Scott Keith, Ana Maria Lopez, and Meghan Butryn. "Abstract P4-11-32: Change in body mass index in breast cancer survivors." Cancer Research 82, no. 4_Supplement (February 15, 2022): P4–11–32—P4–11–32. http://dx.doi.org/10.1158/1538-7445.sabcs21-p4-11-32.
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Abstract Background: Obesity is associated with an increased risk of breast cancer recurrence and poor survival. Obesity rate in adults in the city of Philadelphia is high, with non-Hispanic blacks and Hispanics having the highest rates. We sought to evaluate changes in body mass index (BMI) in breast cancer survivors within the first 2 years from initial encounter for a breast cancer (BC) diagnosis (dx), and investigate factors that may correlate with a change in BMI. Methods: We identified 5,423 BC patients (pts) in our electronic medical record, (1/2015-present), using ICD-10 code C50.X. We then selected pts with BMI values at the three-time points: baseline, 1 year and 2 year intervals from baseline. The closest BMI value before the 1st encounter within 6 months prior to BC dx was considered as the baseline BMI. BMI at 1 year +/- 3 months after the BC dx was considered 1-year interval BMI. BMI at 2 years +/- 6 months after the BC dx was considered 2-year interval BMI. Subjects needed baseline BMI and at least 1 year or 2 year follow-up BMI for inclusion. After all BMI exclusions, 630 pts were included in the study cohort. We used a mixed effects model to predict BMI changes as a linear function of association with time, sex, race and ethnicity, age at BC dx, baseline BMI, treatments (i.e., chemotherapy [CT], endocrine therapy [ET], or immunotherapy [IO] and the interaction of race and ethnicity and treatment in estimating mean change of BMI. The significance level of all tests was set a priori to the 0.05 level. Results: The mean age at BC dx was 61 years; pts identified were mostly white, non-Hispanic/Caucasian (55%), or Black/African American (AA) (34%). By BMI category, we did not observe any substantial difference in the mean age at BC dx and gender distribution (p = 0.81 for age and p = 0.86 for gender). However, the distributions of race and ethnicity differed among BMI categories (p < .01) where the percentage of Black/AA pts was high in the BMI ≥ 30 category. Black/AA pts receiving IO were likely to have BMI change (decrease) compare to white non-Hispanic pts with similar conditions. Black/AA pts receiving no treatment or non IO-treatment were more likely to change BMI (increased, 95% CI: 0.22, 1.03) after BC dx compared to white, non-Hispanic pts. Interestingly, Black/AA pts receiving IO tended to change BMI (decreased) compared to Black/AA pts not receiving IO. Conclusion: We observed the interaction effect of race/ethnicity and treatment on BMI change in BC survivors within 2 years after a BC dx, with Black/AA pts more likely to have an increase in BMI. Table 1.Descriptive Statistics Summary, n = 630.VariableALL (n=630)BMI ≤ 24.9 (n=160, 25%)25 ≤ BMI ≤ 29.9 (n=180, 29%)BMI ≥ 30 (n=290, 46%)p-valueAge at 1st Encounter with BC dx, mean (SD)61.8 (11.8)62.1 (12.5)62.1 (12.1)61.5 (11.2)0.808Sex, n (%)Female625 (99.2)159 (99.4)178 (98.9)288 (99.3)0.857Male5 (0.8)1 (0.6)2 (1.1)2 (0.7)Race & Ethnicity, n (%)White/Caucasian348 (55.2)103 (64.4)106 (58.9)139 (47.9)<.001Black/AA215 (34.1)35 (21.9)48 (26.7)132 (45.5)Hispanic/Latino20 (3.2)5 (3.1)5 (2.8)10 (3.4)Asian/Pacific Islander39 (6.2)17 (10.6)18 (10.0)4 (1.4)American Indian/Alaskan Native2 (0.3)0 (0.0)0 (0.0)2 (0.7)Unknown6 (1.0)0 (0.0)3 (1.7)3 (1.0)BMI (baseline), mean (SD)29.9 (7.1)22.2 (2.0)27.1 (1.4)35.9 (5.7)<.001Treatment (Yes) , n (%)HistoricalCT2 (0.3)1 (0.6)1 (0.6)0 (0.0)0.294ET35 (5.6)7 (4.4)12 (6.7)16 (5.5)0.663IO4 (0.6)2 (1.3)1 (0.6)1 (0.3)0.487BaselineCT20 (3.2)4 (2.5)7 (3.9)9 (3.1)0.815ET54 (8.6)16 (10.0)15 (8.3)23 (7.9)0.742IO11 (1.7)5 (3.1)2 (1.1)4 (1.4)0.3111 yearCT154 (24.4)41 (25.6)42 (23.3)71 (24.5)0.886ET309 (49.0)73 (45.6)93 (51.7)143 (49.3)0.535IO29 (4.6)10 (6.3)8 (4.4)11 (3.8)0.4892 yearsCT71 (11.3)20 (12.5)15 (8.3)36 (12.4)0.337ET231 (36.7)50 (31.3)73 (40.6)108 (37.2)0.198IO32 (5.1)7 (4.4)4 (2.2)21 (7.2)0.051 Citation Format: Maysa Abu-Khalaf, Fnu Nikita, Ayako Shimada, Hannah Hackbart, Dina Alnabulsi, Scott Keith, Ana Maria Lopez, Meghan Butryn. Change in body mass index in breast cancer survivors [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P4-11-32.
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Holum, Parker Jayce, Chelsea Palmer, Xiangqing Sun, Samyukta Venkatesh, Matthew Devall, Gregory Cooper, Steven M. Powell, Cynthia Yoshida, and Li Li. "Adult BMI change over time and risk of colorectal adenoma." Journal of Clinical Oncology 41, no. 4_suppl (February 1, 2023): 68. http://dx.doi.org/10.1200/jco.2023.41.4_suppl.68.
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68 Background: Obesity and adult weigh gain are established risk factors for colorectal cancer (CRC). Few studies have investigated the association between adult body weight change over time and risk of colorectal adenoma. We hypothesize adult BMI change over time is associated with risk in the development of colorectal adenomas. Methods: We tested this hypothesis in 2,993 patients undergoing screening colonoscopy from 2007–2017. Weight at age 20, 30, 40, and 50 were self-reported via computer assisted personal interviews. Height and weight at recruitment were measured at the time of colonoscopy exam. BMI (kg/m2) change was calculated as the difference of BMI at recruitment from the BMI estimate for each of the age periods. Results: Of the 2,993 patients, 984 had pathologically confirmed diagnosis of colon adenoma. Multivariate logistic regression adjusted for potential confounders and BMI at recruitment showed statistically significant increase of risk of adenoma with increase of BMI since age 30, age 40, and age 50. Compared to those with BMI change of less than 5, the ORs for those with BMI gain of 5-10 and ≥10 were: 1) 1.16 (0.92-1.46) and 1.48 (1.08-2.03) respectively for change from age 30 (ptrend = 0.05); 2) 1.11 (0.87-1.43) and 1.60 (1.09-2.35) respectively for change from age 40 (ptrend = 0.05); and 3) 1.36 (0.95-1.94) and 2.95 (1.33-6.90) respectively for change from age 50 (ptrend = 0.01). Stratified analysis did not reveal noticeable gender differences. Conclusions: Large adult weight gain over time is an independent risk factor for colorectal adenoma. Our results suggest maintaining healthy body weight throughout adulthood is an important preventive measure against the development of early colorectal neoplasia. [Table: see text]
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Eisenberg, Dan, Andrew J. Duffy, and Robert L. Bell. "Does Preoperative Weight Change Predict Postoperative Weight Loss after Laparoscopic Roux-en-Y Gastric Bypass in the Short Term?" Journal of Obesity 2010 (2010): 1–4. http://dx.doi.org/10.1155/2010/907097.
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Background. Many institutions mandate preoperative weight loss prior to bariatric surgery. This study examines the correlation between preoperative weight change and postoperative success following laparoscopic Roux-en-Y gastric bypass.Methods. We retrospectively studied the correlation between change in BMI before surgery and change in BMI postoperatively, using linear regression analyses and one-way ANOVA, in 256 consecutive gastric bypass patients with 1-year followup.Results. Of 256 patients, 125 lost weight preoperatively (mean % BMI), while 131 maintained or gained weight (mean +1.2% BMI). Postoperatively, there was no significant difference in percent BMI loss between the two groups (34.6% and 34.5%). The percent change in BMI preoperatively did not predict postoperative BMI change after 1 year ().Conclusions. Our study did not show any correlation between preoperative weight change and postoperative weight loss after Roux-en-Y gastric bypass. Therefore, we do not believe that potential patients should be denied bariatric surgery on the basis of their inability to lose weight preoperatively.
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Liu, Yin, Mari Palta, Jodi Barnet, Max Roberts, Erika Hagen, Paul Peppard, and Eric Reither. "Habitual Sleep, Sleep Duration Differential, and Weight Change Among Adults." Innovation in Aging 5, Supplement_1 (December 1, 2021): 35. http://dx.doi.org/10.1093/geroni/igab046.129.
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Abstract We assessed longitudinal associations between diary-measured sleep duration and clinically assessed body mass index (BMI) among 784 men and women enrolled in the Wisconsin Sleep Cohort Study (mean [SD] age = 51.1 [8.0] years at baseline). The outcome was BMI (kg/m2). Key predictors were habitual sleep duration (defined as average weekday nighttime sleep duration) and sleep duration differential (defined as the difference between average weekday and average weekend nighttime sleep duration) at each data collection wave. Men with shorter habitual sleep duration on weekdays had higher BMI than men with longer habitual sleep duration on weekdays. Participants with larger differentials between weekday and weekend sleep duration experienced more rapid BMI gain over time for both men and women. Inadequate sleep, characterized as shorter habitual sleep during weekdays and larger weekday-weekend sleep differential, is positively associated with BMI levels and trajectories among men and women in mid-to-late life.
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Cole, T. J., M. S. Faith, A. Pietrobelli, and M. Heo. "What is the best measure of adiposity change in growing children: BMI, BMI %, BMI z-score or BMI centile?" European Journal of Clinical Nutrition 59, no. 3 (January 12, 2005): 419–25. http://dx.doi.org/10.1038/sj.ejcn.1602090.
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Shin, Ji-Nam. "Body weight, height and body composition are related to change in bone mineral density in Pre- and Postmenopausal Women." Journal of Medicine and Life Science 2, no. 1 (June 1, 2004): 13–21. http://dx.doi.org/10.22730/jmls.2004.2.1.13.
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Objectives: The aim of this study was to determine the relationship between body composition and bone mineral density (BMD), and to provide a concept of ideal body weight reduction.Method: Total 2,128 women were included in this study and 961 of them were premenopausal and 1,167 were postmenopausal. Body composition was measured by automatic analyser, and BMD by bone mineral densitometer at L2, 3, 4, 5 vertebral body level.Result: Tlie prevalences of osteopenia and osteoporosis in premenopausal women were 23,8% and 1.6% respectively, and those in postmenopausal women were 46.1% and 28.1%. Multiple logistc regression analysis showed that age was risk factor for decreased BMD (Exp(B)=1.07 in premenopausal group and 1.16 in postmenopausal group) and weight was protection factor (Exp(B)=0.92 and 0.95 respectively). Women with low Body mass index (BMI) were significantly more likely to have low BMD compared to those with normal BMI (odds ratio(OR)=1.69 premenopausally, 2.11 postmenopausally). Muscle and fat were positively correlated with BMD(premenopausally r=0.293, 0.229 respetively, p<0.001, postmenopausally「=0.215, 0.214, p<0.01) after age adjusted. After body weight adjusted, waist-hip ratio (WHR) was negatively correlated with BMD (pre r=0.185, p<0.01, post r=0.293, p<0.05). Fat free mass, muscle, mineral were positively correlated with BMD in normal BMI group, and fat % and WHR were negatively correlated in the same group, espetially postmenopausally.Conclusion: Body weight reduction program should include comrehensive body compostion control to prevent osteoporosis.
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Park, Susan, Soo-Min Jeon, Sun-Young Jung, Jinseub Hwang, and Jin-Won Kwon. "Effect of late-life weight change on dementia incidence: a 10-year cohort study using claim data in Korea." BMJ Open 9, no. 5 (May 2019): e021739. http://dx.doi.org/10.1136/bmjopen-2018-021739.
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BackgroundThe association between body mass index (BMI) in late-life and dementia risk remains unclear. We investigated the association between BMI changes over a 2-year period and dementia in an elderly Korean population.MethodsWe examined 67 219 participants aged 60–79 years who underwent BMI measurement in 2002/2003 and 2004/2005 as part of the National Health Insurance Service-Health Screening Cohort. Baseline characteristics including BMI, socioeconomic status and cardiometabolic risk factors were measured at baseline (2002/2003). The difference between BMI at baseline and at the next health screening (2004/2005) was used to calculate the BMI change. After 2 years, the incidence of dementia was monitored for a mean 5.3 years from 2008 to 2013. Multivariate HRs for dementia incidence were estimated on the basis of baseline BMI and its changes after adjusting for various other risk factors. A subgroup analysis was conducted to determine the effects of baseline BMI and BMI changes.ResultsWe demonstrated a significant association between late-life BMI changes and dementia in both sexes (men: >−10% HR=1.26, 95% CI 1.08 to 1.46, >+10% HR=1.25, 95% CI 1.08 to 1.45; women: >−10% HR=1.15, 95% CI 1.03 to 1.29, >+10% HR=1.17, 95% CI 1.05 to 1.31). However, the baseline BMI was not associated with dementia, except in underweight men. After stratification based on the baseline BMI, the BMI increase over 2 years was associated with dementia in men with a BMI of <25 kg/m2and women with a BMI of 18.5–25 kg/m2, but not in the obese subgroup in either sex. However, BMI decrease was associated with dementia in those with a BMI of ≥18.5 kg/m2, but not in the underweight subgroup in either sex.ConclusionBoth weight gain and weight loss may be significant risk factors associated with dementia. Continuous weight control and careful monitoring of weight changes are necessary to prevent dementia development.
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Wang, Yiqing, Annie Green Howard, Linda S. Adair, Huijun Wang, Christy L. Avery, and Penny Gordon‐Larsen. "Waist Circumference Change is Associated with Blood Pressure Change Independent of BMI Change." Obesity 28, no. 1 (November 22, 2019): 146–53. http://dx.doi.org/10.1002/oby.22638.
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Power, Brian D., Helman Alfonso, Leon Flicker, Graeme J. Hankey, Bu B. Yeap, and Osvaldo P. Almeida. "Changes in body mass in later life and incident dementia." International Psychogeriatrics 25, no. 3 (November 14, 2012): 467–78. http://dx.doi.org/10.1017/s1041610212001834.
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ABSTRACTBackground: There is ongoing debate about whether a decline in body mass represents a true risk factor for dementia, whether it is a phenotypic marker of incipient dementia, or perhaps a marker of another process that increases dementia risk. This study was designed to determine if changes in body mass index (BMI) in later life are associated with hazard of incident dementia over a follow-up period of up to eight years.Methods: Method followed was a prospective cohort study of 4,181 men aged 65–84 years, resident in Perth, Australia. The exposure of interest was change in BMI measured between 1996–1998 and 2001–2004. The outcome was incident dementia, established using the Western Australia Data Linkage System until 2009. We used Cox regression models to establish crude and adjusted hazard of dementia for change in BMI.Results: Compared with men with a stable BMI, those with a decrease in BMI >1 kg/m2 had a higher adjusted hazard of dementia (hazard ratio (HR) = 1.89, 95% CI = 1.32–2.70). The cumulative hazard of dementia over follow-up for changes in BMI was greatest for men with a decrease in BMI >1 kg/m2; this trend was apparent for men in all BMI categories (underweight, normal, overweight, obese). A reverse “J-shaped” association between BMI change and incident dementia was observed, with the lowest dementia rate being for men whose BMI remained stable.Conclusions: Men who maintained a stable body mass had the lowest incidence of dementia. Further studies are needed to clarify causality and assess feasibility of interventional studies to preserve body mass in aging men.
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Klepaker, Geir, Paul Keefer Henneberger, Kjell Torén, Cathrine Brunborg, Johny Kongerud, and Anne Kristin Møller Fell. "Association of respiratory symptoms with body mass index and occupational exposure comparing sexes and subjects with and without asthma: follow-up of a Norwegian population study (the Telemark study)." BMJ Open Respiratory Research 9, no. 1 (March 2022): e001186. http://dx.doi.org/10.1136/bmjresp-2021-001186.
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BackgroundOccupational exposure and increased body mass index (BMI) are associated with respiratory symptoms. This study investigated whether the association of a respiratory burden score with changes in BMI as well as changes in occupational exposure to vapours, gas, dust and fumes (VGDF) varied in subjects with and without asthma and in both sexes over a 5-year period.MethodsIn a 5-year follow-up of a population-based study, 6350 subjects completed a postal questionnaire in 2013 and 2018. A respiratory burden score based on self-reported respiratory symptoms, BMI and frequency of occupational exposure to VGDF were calculated at both times. The association between change in respiratory burden score and change in BMI or VGDF exposure was assessed using stratified regression models.ResultsChanges in respiratory burden score and BMI were associated with a β-coefficient of 0.05 (95% CI 0.04 to 0.07). This association did not vary significantly by sex, with 0.05 (0.03 to 0.07) for women and 0.06 (0.04 to 0.09) for men. The association was stronger among those with asthma (0.12; 0.06 to 0.18) compared with those without asthma (0.05; 0.03 to 0.06) (p=0.011). The association of change in respiratory burden score with change in VGDF exposure gave a β-coefficient of 0.15 (0.05 to 0.19). This association was somewhat greater for men versus women, with coefficients of 0.18 (0.12 to 0.24) and 0.13 (0.07 to 0.19), respectively (p=0.064). The estimate was similar among subjects with asthma (0.18; –0.02 to 0.38) and those without asthma (0.15; 0.11 to 0.19).ConclusionsIncreased BMI and exposure to VGDF were associated with increased respiratory burden scores. The change due to increased BMI was not affected by sex, but subjects with asthma had a significantly larger change than those without. Increased frequency of VGDF exposure was associated with increased respiratory burden score but without statistically significant differences with respect to sex or asthma status.
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El-Khairy, Lina, Stein E. Vollset, Helga Refsum, and Per M. Ueland. "Predictors of Change in Plasma Total Cysteine: Longitudinal Findings from the Hordaland Homocysteine Study." Clinical Chemistry 49, no. 1 (January 1, 2003): 113–20. http://dx.doi.org/10.1373/49.1.113.
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Abstract Background: Total cysteine (tCys) in plasma has recently been linked to cardiovascular risk and is also associated with cardiovascular risk factors, including body mass index (BMI) and cholesterol. Changes and predictors of change in tCys concentrations over a mean follow-up time of 6.0 (5.2–7.2) years were assessed in this study. Methods: Baseline data from the Hordaland Homocysteine Study recorded in 1992–1993 included tCys, total homocysteine (tHcy), and various lifestyle and cardiovascular risk factors. In 1998–1999, the same measurements were repeated in 3732 individuals born in 1950–1951 and 3339 individuals born in 1925–1927. Most of the statistical analyses were done separately in the four age and sex groups. Results: The overall mean values of tCys were higher at follow-up [mean (SD), 296 (41) μmol/L] than at baseline [278 (36.5) μmol/L]; P <0.0001. The mean percentage of increase in tCys in the different age and sex groups ranged from 4.9% to 8.5%. There was a significant correlation between the tCys values measured on the two occasions (Spearman correlation coefficient, 0.55–0.59 in the different age and sex groups; P <0.0001). The change in tCys correlated with changes in BMI, cholesterol, and diastolic blood pressure in the younger age group, whereas only changes in BMI predicted changes in tCys in the older age group. Conclusions: tCys increased in the 6 years between the two measurements. Factors related to the baseline tCys values, including BMI and the change in BMI, predicted the tCys changes over time.
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Blake-Gumbs, Lyla, Zhengyi Chen, Cheryl L. Thompson, Nathan A. Berger, Thomas C. Tucker, and Li Li. "Adult BMI Change and Risk of Colon Cancer in Postmenopausal Women." Journal of Obesity 2012 (2012): 1–8. http://dx.doi.org/10.1155/2012/857510.
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Purpose. We recently reported an association of adult BMI change with colon cancer risk. Here, we sought to further explore this association with respect to postmenopausal HRT use in a larger study population.Methods. We included 1,457 postmenopausal women participating in an ongoing population-based case-control study of colon cancer.Results. We confirmed a previously reported association of adulthood weight gain and increased risk of colon cancer: compared to those with <5 kg/m2change of BMI, women who reported moderate (5–10 kg/m2) and large (>10 kg/m2) BMI changes since their 20s had OR estimates of 1.54 (95% CI = 1.09–2.19) and 1.45 (95% CI = 0.90–2.33), respectively (Pfor trend = 0.05). Stratified analyses showed that this association was limited to HRT nonusers: ORs were 1.77 (95% CI = 1.02–3.05) and 2.21 (95% CI = 1.09–4.45), respectively (Pfor trend = 0.03), for BMI changes occurring between the 20s decade and time of recruitment among non-users. Similar associations were observed for BMI changes since the 30s decade. There was no association among HRT users.Conclusion. Our results suggest early adulthood weight gain increases colon cancer risk in postmenopausal women who do not use HRT.
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Mäkelburg, Anja B. U., Elke S. Hoendermis, Nic J. G. M. Veeger, J. C. Kluin-Nelemans, and Karina Meijer. "Change in Body-Mass-Index and Persisting Symptoms After Pulmonary Embolism." Blood 120, no. 21 (November 16, 2012): 3389. http://dx.doi.org/10.1182/blood.v120.21.3389.3389.
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Abstract Abstract 3389 Introduction Two third of patients experience persisting symptoms after pulmonary embolism (PE). No distinct (cardiopulmonary) pathology is detectable in most of them. We previously reported that patients with persisting symptoms had a higher body-mass-index (BMI). In this study, we evaluated whether patients developing persisting symptoms had a higher BMI at time of PE or a larger gain of weight than patients without persisting symptoms, or both. Methods In patients at least one year after PE, height and weight were measured. Medical charts were reviewed for weight at time of PE. Patients were regarded as overweight if BMI was 25–30 kg/m2 and as obese with a BMI >30 kg/m2. Patients were classified as having increased tiredness when they reported any increase in tiredness with or without loss of condition after PE; their daily routine had to be unchanged. Patients were classified as having decreased performance when reporting any change in daily routine due to residual symptoms following PE. All other patients were classified as having no symptoms. Results Between May 2008 and December 2010 129 patients were evaluated. Median age at time of PE was 52.2 (range 20.8–86.7) years and median time passed since PE was 2.0 (range 1.0–14.9) years, 55 (43%) were female. Median BMI at time of PE was 27.5 (range 17.3–46.1) kg/m2. At evaluation for this study, median BMI was 28.1 (range 17.9–50.3) kg/m2. Median gain in weight between PE and evaluation was 3.0 (range −19.0–28.0) kg. This resulted in a median increase in BMI of 0.9 (range −5.4–9.0) kg/m2. In asymptomatic patients, median BMI was unchanged at 26.6 (range 17.9–43.5) kg/m2. In patients with increased tiredness BMI increased from 27.6 (range 18.7–42.1) kg/m2 to 28.4 (range 20.2–46.4) kg/m2, and in patients with decreased performance from 27.9 (range 20.7–46.1) kg/m2 to 28.9 (range 21.9–50.3) kg/m2 (p=0.049). In the asymptomatic group percentage of patients with normal BMI remained 35%. In the symptomatic groups BMI decreased from 28% to 21% and from 24% to 16%, respectively. Percentage of obese patients increased from 23% to 29% in asymptomatic patients, and from 33% and 32% it increased to 37% in both, patients with increased tiredness and in those with decreased performance. Median gain in weight was 2.0 (range −19.0–28.0) kg vs. 3.0 (range −15.0–27.0) kg vs. 3.8 (range −6.0–19.0) kg, respectively. Women more often had persistent symptoms. Females accounted for 38% of asymptomatic patients, in symptomatic patients 28% with increased tiredness and 66% with decreased performance were female. This correlated with a higher percentage of obese women (40%) than men (20%) at time of PE, p=0.009. At time of evaluation, 42% of women and 28% of men were obese, p=0.057. No differences were observed between women and men regarding change in weight or BMI. Conclusion Patients with persisting symptoms were heavier than those without symptoms. This was explained by both a higher BMI at PE, and a greater gain in weight during follow-up. Patients without persisting symptoms had no increase in median BMI. Disclosures: No relevant conflicts of interest to declare.
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Redenius, Rachel, Carli Murphy, Erin O'Neill, Majed Al-Hamwi, and Sarah Nath Zallek. "Does CPAP Lead to Change in BMI?" Journal of Clinical Sleep Medicine 04, no. 03 (June 15, 2008): 205–9. http://dx.doi.org/10.5664/jcsm.27181.
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Fransson, Eleonor I., G. David Batty, Adam G. Tabák, Eric J. Brunner, Meena Kumari, Martin J. Shipley, Archana Singh-Manoux, and Mika Kivimäki. "Association between Change in Body Composition and Change in Inflammatory Markers: An 11-Year Follow-Up in the Whitehall II Study." Journal of Clinical Endocrinology & Metabolism 95, no. 12 (December 1, 2010): 5370–74. http://dx.doi.org/10.1210/jc.2010-0730.
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Context: Obesity is associated with low-grade inflammation, but the long-term effects of weight change on inflammation are unknown. Objective: The aim was to examine the association of change in weight, body mass index (BMI), and waist circumference with change in C-reactive protein (CRP) and IL-6 and to assess whether this association is modified by baseline obesity status. Design and Setting: The design was a prospective cohort study among civil servants (the Whitehall II Study, UK). We used data from two clinical screenings carried out in 1991–1993 and 2002–2004 (mean follow-up, 11.3 yr). Participants: We studied 2496 men and 1026 women [mean age, 49.4 (sd = 6.0) yr at baseline] with measurements on inflammatory markers and anthropometry at both baseline and follow-up. Main Outcome Measures: We measured change in serum CRP and IL-6 during follow-up. Results: The mean increases in CRP and IL-6 were 0.08 [95% confidence interval (CI), 0.07–0.09] mg/liter and 0.04 (95% CI, 0.03–0.05) pg/ml per 1-kg increase in body weight during follow-up. Study members with a BMI less than 25 kg/m2 at baseline had an average increase in CRP of 0.06 (95% CI, 0.05–0.08) mg/liter per 1-kg increase in body weight, whereas the increase in those who were overweight (25 ≤ BMI < 30 kg/m2) and obese (BMI ≥30 kg/m2) was greater: 0.08 (95% CI, 0.06–0.09) mg/liter and 0.11 (95% CI, 0.07–0.14) mg/liter, respectively (P value for interaction = 0.002). Similar patterns were observed for changes in BMI and waist circumference. Conclusions: Those who were overweight or obese at baseline had a greater absolute increase in CRP per unit increase in weight, BMI, and waist circumference than people who were normal weight.
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Duchin, Ofra, Constanza Marin, Mercedes Mora-Plazas, and Eduardo Villamor. "Maternal body image dissatisfaction and BMI change in school-age children." Public Health Nutrition 19, no. 2 (April 30, 2015): 287–92. http://dx.doi.org/10.1017/s1368980015001317.
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AbstractObjectiveParental body image dissatisfaction (BID) is associated with children’s weight in cross-sectional studies; however, it is unknown whether BID predicts development of adiposity. The objective of the present study was to investigate the associations between maternal dissatisfaction with her or her child’s body and children’s BMI trajectories.DesignLongitudinal study. Maternal dissatisfaction (BID) with her and her child’s body was calculated based on ratings of Stunkard scales obtained at recruitment, as current minus desired body image. Children’s height and weight were measured at baseline and annually for a median of 2·5 years. Mixed-effects models with restricted cubic splines were used to construct sex- and weight-specific BMI-for-age curves according to maternal BID levels.SettingPublic primary schools in Bogotá, Colombia.SubjectsChildren (n 1523) aged 5–12 years and their mothers.ResultsAfter multivariable adjustment, heavy boys and thin girls whose mothers desired a thinner child gained an estimated 1·7 kg/m2 more BMI (P=0·04) and 2·4 kg/m2 less BMI (P=0·004), respectively, between the age 6 and 14 years, than children of mothers without BID. Normal-weight boys whose mothers desired a thinner child’s body gained an estimated 1·8 kg/m2 less BMI than normal-weight boys of mothers without BID (P=0·02). Maternal BID with herself was positively related to children’s BMI gain during follow-up.ConclusionsMaternal BID is associated with child’s BMI trajectories in a sex- and weight-specific manner.
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Narayan, M., U. Ahmed, C. R. Bachu, and S. Read. "Risperidone and weight change in children with learning disability. A retrospective study." European Psychiatry 26, S2 (March 2011): 897. http://dx.doi.org/10.1016/s0924-9338(11)72602-5.
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AimRisperidone has been recommended for the management of disruptive behaviour disorders in children with learning disabilities. This study explored the effects of Risperidone on absolute body weight in children with learning disabilities who received Risperidone for disruptive behaviour disorders.MethodologyData was collected for children (n = 70) with learning disabilities who were prescribed Risperidone for disruptive behaviour disorders in out patient clinic. Weight, height and BMI were recorded at the first appointment and at the follow up for up to one year. Data was analysed to find any changes in weight and BMI during the course of treatment with Risperidone.ResultsMean weight gain for the sample was 6.1 kg (sd = 2.7), 1.7 kg more than expected in one year which was statistically significant (t = 6.2, df = 69, p < 0.001). Mean BMI change was 1.51 kg; significantly larger than the mean expected BMI change of 0.62 of this sample (t = 4.98, df = 1.6, P = 0.001). Change in BMI was more for girls, 2.17 (sd = 1.00) compared with boys 1.36 (sd = 1.18), but this was not significant (t = 1.90, df = 49, p = 0.06). There is no significant relationship between Risperidone dose and weight gain (Pearson's r = 0.21, p = 0.42) and BMI (Pearson's r = 0.03, p = 1.00).ConclusionRisperidone should be used with caution in children where weight gain could have long lasting impact. Prescribing clinicians should obtain baseline measures of weight, height, BMI and monitor them at regular intervals. Emphasis should be placed on life style interventions such as diet, physical activities etc. Further comparable studies with larger sample sizes using more homogenous diagnostic samples are needed.
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Berkey, Catherine S., and Graham A. Colditz. "Adiposity in Adolescents: Change in Actual BMI Works Better Than Change in BMI z Score for Longitudinal Studies." Annals of Epidemiology 17, no. 1 (January 2007): 44–50. http://dx.doi.org/10.1016/j.annepidem.2006.07.014.
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Thielke, Stephen. "Patterns of Weight Change in Aging and Dying." Innovation in Aging 4, Supplement_1 (December 1, 2020): 491. http://dx.doi.org/10.1093/geroni/igaa057.1587.
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Abstract Little research has characterized the natural history of weight change in older adults. Different changes may occur during aging and dying. We analyzed 18 years of weight measures from a cohort of 736,361 Veterans, all of whom had died at age 70 or older. We produced summary measures that accounted for both chronological age and number of years before death. Several clear population-level trends appeared. (1) The average weight of the sample declined across all ages at a rate of about 0.18 BMI points per year. (2) Starting about seven years before death, the amount of loss began to accelerate, reaching a decline of 0.75 BMI points in the year before death. (3) Changes in weight relative to years of remaining life were independent of chronologic age. People who died at age 70 experienced, on average, the same type and duration of terminal decline as did those who died at age 95. (4) The dying process involved a cumulative loss of about 1.3 BMI points. (5) The distribution of weights during advancing age both declined and narrowed. (6) Disproportionate deaths occurred at the lower BMI ranges (below a BMI of 24), and especially below 18, regardless of age. (7) The finding in #5 is explained by the entire cohort losing weight, with death of the thinnest members. These findings argue for examining survival time in studies of weight change. They indicate that weight loss may be a natural part of dying, rather than a risk factor for it.
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Hamilton, Catherine L., Edward T. Riley, and Sheila E. Cohen. "Changes in the Position of Epidural Catheters Associated with Patient Movement." Anesthesiology 86, no. 4 (April 1, 1997): 778–84. http://dx.doi.org/10.1097/00000542-199704000-00007.
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Background Epidural catheter movement has been noted with change of patient position and can result in inadequate anesthesia. This study was designed to measure movement and to develop a technique that minimizes catheter displacement. Methods In 255 parturients requesting epidural anesthesia for labor or cesarean section, a multiorificed lumbar epidural catheter was inserted with the patient in the sitting flexed position. The distance to the epidural space, length of catheter inserted, and amount of catheter position change as the patient moved from the sitting flexed to sitting upright and then to the lateral decubitus position were measured before the catheter was secured to the skin. Adequacy of analgesia, the need for catheter manipulation, and whether the patient was considered obese were noted. Data were grouped according to body mass index (BMI): < 25, 25-30, and > 30 kg/m2. Results The groups did not differ with respect to the length of catheter initially inserted or changes in catheter position between initial taping and removal. The distance to the epidural space differed significantly among the groups, increasing with greater BMI. Catheters frequently appeared to be drawn inward with position change from the sitting flexed to lateral decubitus position, with the greatest change seen in patients with BMI > 30. Only nine catheters were associated with inadequate analgesia, four of which were replaced. No analgesic failures occurred in the BMI > 30 group. In patients judged by the anesthesiologist to be obese or to have an obese back, BMI was greater, and distance to the epidural space and the magnitude of catheter movement with position change were greater than in those who were not obese. Conclusions Epidural catheters moved a clinically significant amount with reference to the skin in all BMI groups as patients changed position. If catheters had been secured to the skin before position change, many would have been pulled partially out of the epidural space. To minimize the risk of catheter displacement, particularly in obese patients, we recommend that multiorificed catheters be inserted at least 4 cm into the epidural space and that patients assume the sitting upright or lateral position before securing the catheter to the skin.
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Levy, Jacob J., Whitney J. Statham, and Laura VanDoren. "BMI Changes among Marching Artists: A Longitudinal Study." Medical Problems of Performing Artists 28, no. 4 (December 1, 2013): 236–41. http://dx.doi.org/10.21091/mppa.2013.4045.
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In a series of longitudinal analyses, we examined body mass index (BMI) of drum and bugle corps performers at the beginning (Time 1) and end (Time 2) of a competitive season and again at a 1-year follow-up (Time 3). Utilizing an archival database, BMI data were recorded for 501 marching arts performers, representing four world-class drum and bugle corps. Significant reductions in BMI were found between Time 1 and Time 2 for performers in all sections (i.e., brass, percussion, and color guard). Archival data from 92 performers, representing three World-Class drum and bugle units, revealed BMI significantly increased from Time 2 to Time 3. In an effort to identify possible personal influences on the changes in BMI found between Times 2 and 3, 50 performers from one drum and bugle corps provided archival data on a measures of performers’ athletic identity (i.e., the strength and exclusivity of one’s identification with the athlete role) along with BMI. Correlational analyses revealed that performers’ athletic identity negatively related to BMI change from Time 1 and Time 3 and Times 2 and 3 (i.e., stronger athletic identity, lower BMI change). Practical implications are discussed.
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Cole, T. J., M. S. Faith, A. Pietrobelli, and M. Heo. "Erratum: What is the best measure of adiposity change in growing children: BMI, BMI %, BMI z-score or BMI centile?" European Journal of Clinical Nutrition 59, no. 6 (June 2005): 807. http://dx.doi.org/10.1038/sj.ejcn.1602155.
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Pak, Victoria, David Maislin, Brendan Keenan, Raymond Townsend, Bryndis Benediktsdottir, Xiaofeng Guo, Allan Pack, Thorarinn Gislason, and Samuel Kuna. "455 Obesity modifies the effect of 4 months of CPAP on glucose levels in adults with obstructive sleep apnea." Sleep 44, Supplement_2 (May 1, 2021): A180. http://dx.doi.org/10.1093/sleep/zsab072.454.
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Abstract Introduction Continuous positive airway pressure (CPAP) therapy may improve insulin sensitivity and glucose tolerance seen in individuals with obstructive sleep apnea (OSA), however there is a lack of studies on whether obesity modifies the effect. We examined the baseline and follow-up levels of insulin and glucose following 4 months of CPAP treatment among participants with body mass index (BMI) <30, 30≤ BMI<35, and BMI≥35 kg/m2. Methods We identified 221 adults (84% males) with newly diagnosed OSA in the Penn Icelandic Sleep Apnea (PISA) Study, with a mean (±SD) BMI 31.7 +- 4.2 kg/m2 and apnea-hypopnea index (AHI) of 35.7+-15.6 events/hour. Associations between changes in natural log of the biomarkers within BMI groups were explored, controlling for a priori baseline covariates of age, baseline BMI, race, sex, site, and current smoking status. Results The mean proportional change (from baseline to follow-up) in log-transformed glucose in CPAP adherent participants was significantly larger in the BMI ≥35 and 30≤ BMI<35 groups compared to BMI <30. Within the BMI ≥35 group, the baseline to follow up increase in glucose post-CPAP was 1.08 (95% CI 1.01–1.15), while there were no significant changes in the other 2 BMI groups. A mediation analysis was performed with models including BMI change, and glucose was found to be significantly different between groups. There was no statistically significant association for insulin. Conclusion Our findings show that obesity modifies the effect of four months of CPAP on glucose levels. Support (if any) 1P01-1HL094307
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Abdi, Hengameh, Elham Kazemian, Safoora Gharibzadeh, Atieh Amouzegar, Ladan Mehran, Maryam Tohidi, Zahra Rashvandi, and Fereidoun Azizi. "Association between Thyroid Function and Body Mass Index: A 10-Year Follow-Up." Annals of Nutrition and Metabolism 70, no. 4 (2017): 338–45. http://dx.doi.org/10.1159/000477497.
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Background/Aims: We aimed to evaluate the association between change in thyroid function tests within the euthyroid range and body mass index (BMI) in persons with normal weight at baseline. Methods: This study investigated 1,100 normal-weight euthyroid persons in a population-based cohort study, Tehran Thyroid Study. BMI was calculated and serum concentrations of thyrotropin (TSH) and free T4 (FT4) were assayed at baseline and after 10 years of follow-up. We evaluated the relationship between thyroid and obesity based on 2 definitions for outcome: (1) a binary outcome as BMI <25 or ≥25 kg/m2, and (2) a multinomial outcome as normal BMI, overweight, and obese. Results: A total of 569 women and 531 men, aged 36.3 ± 13.5 years, were included. Modified Poisson regression analysis for binary outcome, after adjustment for age, sex, smoking, and anti-thyroid peroxidase antibody status, revealed a negative association between delta serum FT4 and follow-up BMI (relative risk 0.55 [95% CI 0.37-0.80]) without any significant association between change in serum TSH and follow-up BMI. However, in multinomial logistic regression analysis, we found no relationship between delta serum FT4 or TSH and follow-up BMI categories, for either overweight or obese vs. normal-weight participants. Conclusions: In normal-weight euthyroid individuals, changes in serum concentrations of FT4, but not TSH, may contribute to change in body weight.
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Chhillar, Ekta, Manju Puri, Rajesh Kumar Sinha, and Praveen Kumar. "Comparison between body mass index and mid upper arm circumference for classifying nutritional status of pregnant women: a prospective cohort study." International Journal Of Community Medicine And Public Health 8, no. 5 (April 27, 2021): 2293. http://dx.doi.org/10.18203/2394-6040.ijcmph20211748.
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Background: BMI is used to assess nutritional status of pregnant women however weight gain during pregnancy confounds the nutritional status later in pregnancy. Unlike weight, MUAC does not undergo significant change as the pregnancy advances. We aim to compare the changes in BMI and MUAC in pregnant women over various trimesters to assess whether change in MUAC is less compared to weight.Methods: In this prospective observations study, BMI and MUAC measurements were taken of 300 pregnant women during different trimesters. Chi-square tests were conducted to assess associations between socio-demographic indicators and nutritional status. Correlation coefficients were calculated between BMI and MUAC over three trimesters. ANOVA tests were conducted on BMI and MUAC to assess their respective mean differences over three trimesters.Results: Mean difference of 0.43 cm (3.2%) was noted in MUAC compared to 5.32 kg/m2 (23.14%) in BMI from first to third trimester. No significant differences were observed in mean MUACs between first and second (p=0.326) and second and third trimesters (p=0.143) but, it was significantly different between first and third trimesters (p=0.003). Significant differences were observed in mean BMIs between first and second (p=0.05), second and third (p<0.001) and first and third trimesters (p<0.001). Correlation between BMI and MUAC were positive and significant in all three trimesters.Conclusions: Positive correlations were found between BMI and MUAC. Less change was observed in MUAC than BMI over three trimesters. MUAC seems to be a reliable tool for assessing nutritional status of antenatal women.
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MacAlpine, Elle M., Divya Talwar, Eileen P. Storey, Scott M. Doroshow, and J. Todd R. Lawrence. "Weight Gain After ACL Reconstruction in Pediatric and Adolescent Patients." Sports Health: A Multidisciplinary Approach 12, no. 1 (September 5, 2019): 29–35. http://dx.doi.org/10.1177/1941738119870192.
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Background: Adolescent athletes who sustain an anterior cruciate ligament (ACL) tear have significantly reduced activity levels during recovery. Activity level is linked to body mass index (BMI); however, it is unclear how recovery from an ACL reconstruction (ACLR) affects relative BMI and whether these changes persist after return to activity. Hypothesis: Patients’ BMI percentile will significantly increase after ACLR, but will trend toward baseline after return to activity. Study Design: Cross-sectional study. Level of Evidence: Level 3. Methods: A retrospective review of 666 pediatric and adolescent patients who underwent ACLR was performed. Body mass was assessed by evaluating change in BMI percentile at 8 standard-of-care time windows relative to BMI percentile at time of surgery. Linear regression and bivariate and multivariate analyses were used to assess the effect of time window and other demographic factors on the change in BMI percentile. These analyses were rerun after dividing patients by clinical obesity categorization (underweight, normal, overweight, or obese) at time of surgery to assess the effect of preinjury body mass levels. Results: BMI percentile of all BMI categories tended to increase postoperatively, peaking 6 to 9 months after surgery, with a median increase of 1.83 percentile points. After this peak, BMI approached baseline but remained elevated at 0.95 percentile points 2 years postoperatively. Beginning 3 months after surgery, the normal-weight group had significantly larger changes in BMI percentile at each time window, peaking at 4.15 points above baseline at 9 months. This BMI increase among normal-weight patients persisted in the second postoperative year, with a median percentile increase of 2.63 points. Conclusion: Pediatric and adolescent patients, especially those with a normal BMI, undergo significant changes to their BMI during recovery from ACLR. Clinical Relevance: Patients’ failure to return to their presurgical BMI percentile 2 years postoperatively suggests that ACLR may have long-reaching and often unappreciated effects on body mass.