Baseline Body Mass Index Category Research Articles

Abstract P2-11-11: Impact of baseline body mass index (BMI) and weight changes after diagnosis in young women with early breast cancer (BC): A multicenter retrospective study

Abstract Background: Prior studies demonstrated that premenopausal obese women with BC have a poorer prognosis than non-obese patients (pts). We examined time trends in the prevalence of overweight and obesity among young women diagnosed with early BC and assessed the impact of baseline BMI and weight changes in disease outcomes. Patients and methods: Multicenter retrospective cohort study including young women (≤40yrs) diagnosed with stage I-III BC during 2000-2016 treated in two large Belgian hospitals. Data on baseline characteristics, treatment, and survival outcomes were collected. Pts were classified according to baseline BMI into underweight (<18.5 kg/m2), normal weight (18.5-24.9 kg/m2), overweight (25-29.9 kg/m2) and obese (≥30 kg/m2). Landmark analysis at 2y after diagnosis (+/-6 months) was performed to evaluate the impact of weight changes (≥5% from baseline) on disease outcomes. Univariate hazard ratios were calculated for outcomes of interest (invasive disease-free survival [IDFS], distant recurrence-free interval [DRFI], overall survival [OS]). Multivariable analysis adjusting for factors that differed between groups was performed for the analysis of 2 BMI categories. Results: A total of 1,849 eligible pts were included, of whom 1,371 (74.1%) had a BMI recorded: 84 (6.1%) were underweight, 871 (63.5%) had normal weight, 304 (22.1%) were overweight and 112 (8.1%) were obese. Baseline BMI was similar across age groups. Overweight and obese pts had significantly larger tumor size when compared to underweight and normal weight pts (p=0.002) with similar rates of nodal involvement. The proportion of pts diagnosed with a BMI ≥25 significantly increased over time (OR: 1.03; 1.00-1.05 p=0.024). There was no difference in OS, DRFI and IDFS according to baseline BMI when grouping pts in the 4 BMI categories (underweight vs. normal weight vs. overweight vs. obese) or in the 2 BMI categories (underweight/normal weight vs. overweight/obese). Multivariate analysis with 2 BMI categories also did not demonstrate differences in OS, DRFI and IDFS. 1,023 pts had weight registered at 2y follow-up, of whom 360 (35.1%) were overweight, and 107 (10.4%) obese. Regarding weight changes, 117 (11.4%) presented weight loss, 617 (60.4%) stable weight, and 287 (28.1%) had weight gain. Weight gain was significantly associated with the use of endocrine therapy in general (p=0.029) and ovarian function suppression (p<0.001). In pts with baseline BMI ≥25, 59 (18.5%) lost weight, 185 (58%) maintained a stable weight, and 74 (23.2%) continued to gain weight. There was no statistically significant impact of weight changes at 2y on disease outcomes. Conclusions: Our time trend analysis suggests that the prevalence of overweight and obesity among young women with BC is increasing over time, highlighting the need for preventing overweight/obesity. In this retrospective analysis, BMI had no impact on disease outcomes. Prospective studies and analyzes of body composition can add important information in this regard. Weight gain after BC diagnosis was significantly associated with the use of endocrine therapy and ovarian function suppression and is a prevalent issue among young women, with 23% of overweight/obese pts at diagnosis continuing to gain weight. Further studies evaluating weight changes and interventions to prevent weight gain are needed to better inform survivorship programs. Table 1.- Impact of Baseline BMI and weight changes on disease outcomesOverall survival (OS)4 BMI categories (baseline)Hazard ratio2 BMI categories (baseline)Hazard ratioNormal weightReferenceUnderweight/normal weight (BMI<25)ReferenceUnderweight1.37 (0.8-2.2)Overweight1.01 (0.7-.1.3)Overweight/obese (BMI≥25)1.05 (0.7-1.3)Obese1.28 (0.4-1.2)Distant Recurrence-Free Interval (DRFI)Normal weightReferenceUnderweight/normal weight (BMI<25)ReferenceUnderweight0.86 (0.5-1.3)Overweight0.88 (0.6-1.1)Overweight/obese (BMI≥25)0.91 (0.7-1.1)Obese0.94 (0.6-1.3)Invasive disease-free survival (IDFS)Normal weightReferenceUnderweight/normal weight (BMI<25)ReferenceUnderweight0.88 (0.5-1.3)Overweight0.88 (0.6-1.1)Overweight/obese (BMI≥25)0.92 (0.7-1.1)Obese0.99 (0.6-1.4)Weight changes analysisWeight changes categoryHazard ratio for OSHazard ratio for DRFIHazard ratio for IDFSStable weightReferenceReferenceReferenceWeight Loss1.45 (0.9-2.2)1.11 (0.6-1.8)1.05 (0.6-1.6)Weight Gain0.77 (0.5-1.14)0.92 (0.6-1.3)0.92 (0.6-1.2) Citation Format: Maria Alice Franzoi, Kevin Punie, Annouschka Laenen, Boudewijn Dullens, Celia Fernandes Costa, Patrick Neven, Hans Wildiers, Matteo Lambertini, Evandro de Azambuja. Impact of baseline body mass index (BMI) and weight changes after diagnosis in young women with early breast cancer (BC): A multicenter retrospective study [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 P2-11-11.

Abstract PD5-11: Pilot study to assess prolonged nightly fasting in breast cancer survivors (LONGFAST)

Abstract Background: Prior, retrospective analysis of nightly fasting among women with breast cancer suggests that fasting less than 13 hours per night may be associated with higher risk of breast cancer recurrence. Small studies suggest that fasting duration can influence inflammation, obesity, sleep, and other potential mediators of breast cancer recurrence risk. Prolonged overnight fasting is a simple, nonpharmacological behavioral intervention strategy that may be doable for most patients. We designed this pilot study to prospectively evaluate the feasibility of prolonged overnight fasting among breast cancer survivors. Methods: We designed a single-arm, pilot study to evaluate the feasibility of fasting for 13 hours overnight for a 12-week period among women with a history of early stage breast cancer (I to III) who had completed initial cancer therapy at least 6 months prior. Baseline and end of study assessments included measurements of body mass index (BMI), quality of life (QOL) (Functional Assessment of Cancer Therapy - General (FACT-G)), mood (Hospital Anxiety and Depression Scale (HADS)), fatigue (Functional Assessment of Chronic Illness Therapy (FACIT) - Fatigue), levels of physical activity (Godin Leisure-Time Exercise Questionnaire), and blood biomarkers (expanded lipid profile, hemoglobin A1c, C-reactive protein, interleukin-6, tumor necrosis factor alpha, leptin, adiponectin). Patient-reported outcome (PRO) surveys were also administered at 6 weeks. Feasibility was defined as ≥ 60% of participants documenting fasting in the food diary for 13 hours on at least 70% of nights during the study period. Changes in study measures from baseline were evaluated using Wilcoxon signed-rank tests. Results: Between July 2020 and January 2021, we enrolled 40 women with a history of breast cancer. Participants had a median age of 59.9 (range 34.9-76.3) and median time since diagnosis was 4.5 years (range 0.8-20.7). At baseline, BMI was normal (18.5-24.9) in 40.0%, overweight (25-29.9) in 37.5%, and obese (≥30) in 22.5%. Forty-two and a half percent had Stage I cancer, 42.5% stage II, and 15.0% stage III. Sixty-five percent were on hormonal therapy. Ninety-five percent of participants fasted ≥ 13 hours for at least 70% of study days (95% CI 83%-99%). At 6 weeks, there was a statistically significant improvement in anxiety (p=.0007). No other significant changes were seen in PROs. At 12 weeks, there were statistically significant improvements in BMI (p=.0072), anxiety (p=.0141), depression (p=.0048), and fatigue (p=.0105). There was no association between change in BMI during the study and baseline BMI category, age, or endocrine therapy. There was no significant change in overall QOL, physical activity levels, or blood biomarkers at 12 weeks. Conclusions: Prolonged overnight fasting is feasible in the breast cancer population and may improve BMI, mood, and fatigue without a detrimental effect on overall QOL. The data from this study support the need for a larger, longer randomized study of prolonged overnight fasting in the breast cancer population to further evaluate the effects on body composition, mood, QOL, metabolic markers, and risk of recurrence. Table 1.Impact of Prolonged Overnight Fasting among Breast Cancer SurvivorsStudy AssessmentMedian at baselineMedian at 12 weeksMedian within-participant changep-valueBody Mass Index (kg/m2)26.4225.80-0.380.0072HADS - Depression1.001.00-1.000.0048HADS - Anxiety4.504.00-0.500.0141FACIT - Fatigue47.5049.821.000.0105FACT-G - Quality of Life95.2096.840.910.4933Physical Activity Level40.5039.000.000.3340Hemoglobin A1c (mg/dL)5.455.400.000.2758High-density lipoprotein (mg/dL)72.0073.00-2.000.4688Low-density lipoprotein (mg/dL)92.0099.001.000.5626Total Cholesterol (mg/dL)193.00192.003.000.6569C-reactive protein (mg/L)1.500.90-0.100.1043Interleukin-6 (pg/mL)2.001.90-0.300.1213Tumor Necrosis Factor α (pg/mL)0.740.74-0.050.2898Adiponectin (ug/mL)12.0012.000.000.0682Leptin (ng/mL)7.158.30-0.100.8418 Citation Format: Elizabeth K. O'Donnell, Yael N. Shapiro, Amy Comander, Steven J. Isakoff, Beverly Moy, Laura Spring, Seth Wander, Irene Kuter, Jennifer Shin, Jerry Younger, Michelle Specht, Chryssanthi Kourniotis, Carol Sullivan, Loren Winters, Nora Horick, Jeffrey Peppercorn. Pilot study to assess prolonged nightly fasting in breast cancer survivors (LONGFAST) [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 PD5-11.

69. Incidence of metabolic complications among treatment-naïve adults living with HIV-1 randomized to B/F/TAF, DTG/ABC/3TC or DTG+F/TAF after 144 Weeks

BackgroundMetabolic comorbidities including diabetes (DM) and dyslipidemia pose challenges to the long-term care of people with HIV (PWH). Incidence of cardiovascular disease and DM are reported at higher rates in PWH than the general population. Obesity is broadly prevalent in both the general population and PWH, and higher body mass index (BMI) can contribute to metabolic complications. Here we present longer-term follow up on incidence of DM, hypertension (HTN), BMI categorical shifts, and lipid changes over 144 weeks of blinded treatment from two trials of PWH initiating antiretroviral therapy.MethodsWe assessed incidence of metabolic complications in adult PWH in Study 1489: bictegravir/emtricitabine/tenofovir alafenamide (B/F/TAF) vs dolutegravir/abacavir/ lamivudine (DTG/ABC/3TC) and Study 1490: B/F/TAF vs DTG+F/TAF. Treatment-emergent (TE) metabolic comorbidities were defined by standard MedDRA search lists. CDC-defined BMI categories were compared from baseline (BL) to Week 144. Analyses by sex at birth and race were performed, as well as for lipid changes.ResultsAmong 1,274 total participants, median (range) age was 33 years (18-77), 90% men, 33% black. In study 1489, BL prevalence of DM and HTN was 4.5 and 12.1% with TE DM and HTN in B/F/TAF being 0.7% and 10%, and for DTG/ABC/3TC 1.3% and 6.9%, respectively. In study 1490, BL prevalence of DM and HTN was 6.8 and 18.8% with TE DM and HTN in B/F/TAF being 2.1 and 5.8%, and for DTG+F/TAF 2.3 and 6.5%, respectively. BMI shift from Normal to Obese: B/F/TAF 0%, DTG/ABC/3TC 3.2%, p=0.12 (1489) (Table 1); B/F/TAF 2.5%, DTG+F/TAF 2.9% p=1.00 (1490) (Table 2). Subgroup analyses by gender/race showed similar findings for TE DM, HTN, and BMI changes. Median changes from BL fasted lipids were small (Table 1).Table 1§. Studies 1489 and 1490: Metabolic Outcomes from Baseline to Week 144 Table 2±. Shift Table of BMI Category at Week 144 by Baseline BMI Category – Overall ConclusionThrough over 144 weeks of follow up, PWH randomized to initiate B/F/TAF, DTG/ABC/3TC or DTG+F/TAF had low rates of incident DM or HTN-related AEs, with no statistically significant differences by treatment group. BMI changes/categorical shifts from BL did not significantly differ by regimen, and no clinically significant change or difference by regimen in lipids were observed. While data are limited by three years of follow up, they are strengthened by randomized study design of three widely used initial ART regimens.Disclosures Eric Daar, MD, Bristol-Myers Squibb (Consultant)Gilead Sciences Inc. (Consultant, Scientific Research Study Investigator, Advisor or Review Panel member, Research Grant or Support)Janssen (Consultant, Advisor or Review Panel member, Research Grant or Support)Merck (Consultant, Advisor or Review Panel member, Research Grant or Support)Teva (Consultant, Advisor or Review Panel member)ViiV Healthcare (Consultant, Advisor or Review Panel member, Research Grant or Support) Chloe Orkin, MD, Gilead Sciences Inc. (Grant/Research Support, Scientific Research Study Investigator, Other Financial or Material Support)Janssen (Research Grant or Support, Other Financial or Material Support)Merck (Research Grant or Support, Other Financial or Material Support)ViiV Healthcare (Research Grant or Support, Other Financial or Material Support) Paul Sax, MD, Gilead Sciences (Consultant, Grant/Research Support)Janssen (Consultant)Merck (Consultant, Research Grant or Support)ViiV (Consultant, Research Grant or Support) Jeffrey L. Stephens, MD, Gilead Sciences Inc. (Scientific Research Study Investigator, Research Grant or Support) Ellen Koenig, MD, Gilead Sciences Inc. (Scientific Research Study Investigator) Amanda Clarke, MD, Gilead Sciences Inc. (Consultant, Scientific Research Study Investigator, Other Financial or Material Support, Conference attendance sponsorship)ViiV Healthcare (Consultant, Other Financial or Material Support, Conference travel sponsorship) Axel Baumgarten, MD, AbbVie (Advisor or Review Panel member, Speaker’s Bureau)Bristol-Myers Squibb (Advisor or Review Panel member, Speaker's Bureau)Gilead Sciences Inc. (Scientific Research Study Investigator, Advisor or Review Panel member, Speaker's Bureau)Janssen (Speaker’s Bureau)Merck (Advisor or Review Panel member) Cynthia Brinson, MD, Abbvie (Scientific Research Study Investigator)BI (Scientific Research Study Investigator)Gilead Sciences Inc. (Scientific Research Study Investigator, Advisor or Review Panel member, Speaker's Bureau, Personal fees)GSK (Scientific Research Study Investigator)Novo Nordisk (Scientific Research Study Investigator)ViiV Healthcare (Scientific Research Study Investigator, Advisor or Review Panel member, Speaker's Bureau) Moti Ramgopal, MD FIDSA, Abbvie (Scientific Research Study Investigator, Speaker's Bureau)Gilead (Consultant, Scientific Research Study Investigator, Speaker's Bureau)Janssen (Consultant, Scientific Research Study Investigator, Research Grant or Support, Speaker's Bureau)Merck (Consultant, Scientific Research Study Investigator)ViiV (Consultant, Scientific Research Study Investigator, Speaker's Bureau) Hailin Huang, PhD, Gilead Sciences Inc. (Employee, Shareholder) Terry Farrow, MD, Gilead Sciences Inc. (Employee, Shareholder) Jared Baeten, MD, PHD, Gilead Sciences Inc. (Employee, Shareholder) Jason Hindman, PharmD, Gilead Sciences Inc. (Employee, Shareholder) Hal Martin, MD, MPH, Gilead Sciences Inc. (Employee, Shareholder) Kimberly Workowski, MD, Nothing to disclose

Pregnancy Weight Gain and Postpartum Weight Retention in Active Duty Military Women: Implications for Readiness.

Weight gain in pregnancy is expected; however, excessive gestational weight gain and postpartum weight retention (PPWR) can cause long-term changes to a patient's body mass index (BMI) and increase the risk for adverse health outcomes. This phenomenon is understudied in active duty military women, for whom excess weight gain poses challenges to readiness and fitness to serve. This study examines over 30,000 active duty military women with and without preeclampsia to assess changes in BMI postpartum. This is a retrospective analysis of claims data for active duty military women, aged 18-40 years, and experiencing pregnancy during fiscal years 2010-2014. Women with eating disorders, high-risk pregnancy conditions other than preeclampsia, scheduled high-risk medical interventions, or a second pregnancy within 18 months were excluded from the analysis. Height and weight were obtained from medical records and used to calculate BMI. Women with and without preeclampsia were categorized into BMI categories according to the Centers for Disease Control and Prevention classification of underweight (BMI < 18.5), normal weight (BMI 18.5-24.9), overweight (BMI 25.0-29.9), or obese (>30.0). Linear regressions adjusted by age and race were performed to assess differences in prepregnancy weight and weight gain, retention, and change at 6 months postpartum. The greatest number of pregnant, active duty service women were found among ages 18-24 years, White race, Army service, junior enlisted rank, married status, and with no mental health diagnosis. Overall, over 50% of women in normal and preeclamptic pregnancies returned to their baseline BMI postpartum. Women in both populations more often gained than lost weight postpartum. Preeclampsia strongly affected weight retention, with 40.77% of overweight women and 5.33% of normal weight women progressing to postpartum obesity, versus 32.95% of overweight women and 2.61% of normal weight women in the main population. Mental health conditions were not associated with significant weight gain or PPWR. Women with cesarean deliveries gained more weight during pregnancy, had more PPWR, and lost more weight from third trimester to 6 months postpartum. Most women remain in their baseline BMI category postpartum, suggesting that prepregnancy weight management is an opportunity to reduce excess PPWR. Other opportunities lie in readiness-focused weight management during prenatal visits and postpartum, especially for patients with preeclampsia and cesarean sections. However, concerns about weight management for readiness must be carefully balanced against the health of the individual service members.

Early mortality and cardiovascular disease, varied association with body mass index and its changes in insulin-treated diabetes: a nationwide study.

We investigated the hazards of cardiovascular diseases (CVDs) and all-cause death during follow-up according to baseline body mass index (BMI) and percent change in BMI among adults with insulin-treated diabetes. Using the Korean National Health Insurance Service datasets (2002-2017), the hazards of myocardial infarction (MI), stroke, and all-cause mortality during follow-up were analyzed according to baseline BMI and percent change in BMI among adults with insulin-treated diabetes and without baseline CVD and/or malignancy (N = 44,055). At baseline, 67.3% of total subjects were either obese or overweight. During a mean 3.8 years, 1,081 MI and 1,562 stroke cases developed; 2,847 deaths occurred over a mean 3.9 years. Compared with normal weight, overweight and obesity were associated with lower hazards of outcomes [hazard ratio (95% CI): 0.836 (0.712-0.981), 0.794 (0.687-0.917) for MI; 0.829 (0.726-0.946), 0.772 (0.684-0.870) for stroke; 0.740 (0.672-0.816), 0.666 (0.609-0.728) for death, respectively]. Underweight was associated with a higher hazard of all-cause death during follow-up [hazard ratio (95% CI): 2.035 (1.695-2.443)]. When the group with minimum absolute value for percent change in BMI was set as a reference, the relative reduction in BMI was associated with increased hazards of MI, stroke, and all-cause death, and relative increase in BMI was associated with increased hazards of stroke and all-cause death during follow-up. Among adults with insulin-treated diabetes, a high prevalence of overweight and obesity was observed, and baseline BMI category was inversely associated with CVD incidence and all-cause death during follow-up. Both weight loss and gain were associated with increased CVD incidence and all-cause death during follow-up, showing a U-shaped relationship between weight change and outcome. Stable body weight might be a predictor of a lower risk of CVDs and premature death among individuals with insulin-treated diabetes.

Changes in lipidomic profile by anti-retroviral treatment regimen: An ACTG 5257 ancillary study.

High cardiovascular disease risk in people living with HIV is partly attributed to antiretroviral therapy (ART). Lipid response to ART has been extensively studied, yet, little is known how small molecule lipids respond to Integrase inhibitor-based (INSTI-based) compared to Protease inhibitor-based (PI-based) ART regimens.Ancillary study to a phase 3, randomized, open-label trial [AIDS Clinical Trial Group A5257 Study] in treatment-naive HIV-infected patients randomized in a 1:1:1 ratio to receive ritonavir-boosted atazanavir (ATV/r), ritonavir-boosted darunavir (DRV/r) (both PI-based), or raltegravir with Tenofovir Disoproxil Fumarate-TDF plus emtricitabine (RAL, INSTI-based).We examined small molecule lipid response in a subcohort of 75 participants. Lipidomic assays of plasma samples collected pre- and post-ART treatment (48 weeks) were conducted using ultra-performance liquid chromatography coupled to time-of-flight mass spectrometry. The effect of ART regimens was regressed on lipid species response adjusting for the baseline covariates (lipids, age, sex, race, CD4 level, BMI, and smoking). Results were validated in the Centers for AIDS Research Network of Integrated Clinical Systems study (N = 16).Out of 417 annotated lipids, glycerophospholipids (P = .007) and sphingolipids (P = .028) had a higher response to ATV/r and DRV/r compared to RAL. The lysophosphatidylcholine (LPCs(16:1),(17:1),(20:3)) and phosphophatidylcholine species (PCs(40:7),(38:4)) had an opposite response to RAL versus ATV/r in the discovery and validation cohort. The INSTI-based regimen had an opposite response of ceramide species ((d38:1), (d42:2)), PCs((35:2), (38:4)), phosphatidylethanolamines (PEs(38:4), (38:6)), and sphingomyelin(SMd38:1) species compared with the PI-based regimens. There were no differences observed between 2 PI-based regimens.We observed differences in response of small molecule lipid species by ART regimens in treatment-naive people living with HIV.

Effect of dulaglutide 3.0 and 4.5mg on weight in patients with type 2 diabetes: Exploratory analyses of AWARD-11.

AimTo evaluate the impact of dulaglutide 3.0 and 4.5 mg versus 1.5 mg on body weight in patients with type 2 diabetes (T2D) based on exploratory analyses of the AWARD‐11 trial.Materials and MethodsPatients were randomized to once‐weekly dulaglutide 1.5 (n = 612), 3.0 (n = 616) or 4.5 mg (n = 614) for 52 weeks. The primary objective was superiority of dulaglutide 3.0 and/or 4.5 mg over 1.5 mg in HbA1c reduction at 36 weeks. Secondary and exploratory assessments included weight reduction in the overall trial population and baseline body mass index (BMI) and HbA1c subgroups.ResultsAt baseline, patients had a mean age of 57.1 years, HbA1c 8.6% (70 mmol/mol), weight 95.7 kg and BMI 34.2 kg/m2. At 36 weeks, dulaglutide 3.0 and 4.5 mg were superior to 1.5 mg for weight change from baseline (1.5 mg, −3.1 kg; 3.0 mg, −4.0 kg [P = .001]; 4.5 mg, −4.7 kg [P < .001]). Higher dulaglutide doses were associated with numerically greater weight reduction compared with 1.5 mg in each baseline BMI and HbA1c subgroup. Absolute weight reduction increased with increasing BMI category, but percentage weight loss was similar between subgroups. Weight reductions with dulaglutide were greater in patients with lower versus higher baseline HbA1c.ConclusionsIn patients with T2D, inadequately controlled by metformin, incremental weight loss was observed with dulaglutide 1.5, 3.0 and 4.5 mg doses regardless of baseline BMI or HbA1c. Although absolute weight loss was numerically greater in patients with higher baseline BMI, percentage of weight loss was similar between BMI subgroups.

Changes in Body Mass Index Associated with Antiretroviral Regimen Switch Among Treatment-Experienced, Virologically Suppressed People Living with HIV in the United States

With obesity on the rise among people living with HIV (PLWH), there is growing concern that weight gain may result as an undesired effect of antiretroviral therapy (ART). This analysis sought to assess the association between ART regimens and changes in body mass index (BMI) among ART-experienced, virologically suppressed PLWH. ART-experienced, virologically suppressed PLWH ≥18 years of age in the Observational Pharmacoepidemiology Research and Analysis (OPERA) cohort were included for analysis if prescribed a new regimen containing one of the following core agents: dolutegravir (DTG), elvitegravir/cobicistat (EVG/c), raltegravir (RAL), rilpivirine (RPV), or boosted darunavir (bDRV), for the first time between August 1, 2013 and December 31, 2017. Multivariable linear regression was used to assess the association between regimen and mean changes in BMI at 6, 12, and 24 months after switch. In unadjusted analyses, BMI increases ranged from 0.30 kg/m2 (bDRV) to 0.83 kg/m2 (RPV) at 24 months following switch, but gains were observed with every regimen. In adjusted analyses, compared to DTG, only bDRV was associated with a smaller increase in BMI at all time points, while EVG/c and RAL were associated with smaller increases in BMI at 6 months only. Overall, results were consistent in analyses stratified by baseline BMI category. BMI increases were relatively small but followed an upward trend over time in this cohort of treatment-experienced, suppressed PLWH. Gains were attenuated with a longer period of follow-up. BMI gains did not differ by regimens, except for bDRV regimens, which were consistently associated with smaller BMI increases than DTG.

Changes in Body Mass Index Among Antiretroviral Therapy Naïve People Living with HIV in Southeastern Nigeria

The proportion of people living with HIV (PLHIV) who are overweight or obese is rising, leading to a double epidemic of HIV and obesity. The purpose of this retrospective longitudinal study was to examine changes in body mass index (BMI) among PLHIV who were new to antiretroviral therapy (ART) in two states in Southeastern Nigeria. The BMI at baseline and 12 months were compared and the difference in proportions in each BMI category was tested. The association between the BMI at 12 months and the demographic and/or clinical variables was examined using multiway analysis of covariance. The study included 2,146 participants. After 12 months on ART, the number of participants who were obese increased by 135% (81 to 190), while those who were underweight decreased by 130% (306 to 133). Overall, the BMI increased in 30.2% of the participants. Further analysis showed that age (p=.009; &amp;eta;2=.005), baseline BMI (p&amp;lt;.001; &amp;eta;2=.435), baseline regimen (p&amp;lt;.001; &amp;eta;2=.031), HIV stage (p=.039; &amp;eta;2=.007) and CD4 category (p&amp;lt;.001; &amp;eta;2=.012) were all associated with increased BMI after 12 months of ART. Healthcare providers should be mindful of the likelihood of excess weight gain among PLHIV who are on ART and develop a plan to proactively address it.

Effect of tailoring on weight loss among young adults receiving digital interventions: an 18 month randomized controlled trial.

Weight loss outcomes among young adults in technology-based programs have been equivocal. The purpose of this study was to deliver digital weight loss treatments to young adults and examine the 6, 12, and 18 month effects on weight loss. Young adults with overweight/obesity (N = 459; 23.3 ± 4.4 years) were recruited from two university sites and randomly assigned to receive through Facebook and text messaging either personalized (TAILORED; n = 150) or generic (TARGETED; n = 152) weight loss information, messages, and feedback or general healthy body content (e.g., body image, sleep; CONTROL; n = 157). The study was powered to detect a 2.1-kg difference at all time points with the primary outcome being 18 months. There was no overall effect of treatment group on 6, 12, or 18 month weight loss (ps = NS). However, at 6 months, those in TAILORED who were highly engaged (completing >66%) lost more weight compared to CONTROL (-2.32 kg [95% confidence intervals: -3.90, -0.74]; p = .004), with the trend continuing at 12 months. A significant baseline body mass index (BMI) by treatment group interaction (p = .004) was observed at 6 months. Among participants in the lowest baseline BMI category (25-27.5 kg/m2), those in TAILORED lost 2.27 kg (-3.86, -0.68) more, and those in TARGETED lost 1.72 kg (-3.16, -0.29) more than CONTROL after adjusting for covariates. Among participants with a BMI between 27.5 and 30 kg/m2, those in TAILORED lost 2.20 kg (-3.90, -0.51) more than participants in TARGETED. Results did not persist over time with no treatment interaction at 12 or 18 months. Initial body weight should be considered when recommending weight loss treatments for young adults. More intensive interventions or stepped care approaches may be needed for young adults with obesity.

Behavioural change, weight loss and risk of dementia: A longitudinal study

Recent meta-analysis reported higher dementia risks associated with lower body mass index (BMI) and decreasing BMI. We examined to what extent these associations were attenuated by changes in behaviours and local environment. Multilevel discrete time-to-event models examined associations between baseline and change in BMI with dementia detected through prescription medications (source: Department of Human Services), hospitalisations and death certificates among 144,456 participants in the Sax Institute's 45 and Up Study. Models were adjusted for socioeconomic factors and measures of change in adherence to published guidelines for moderate to vigorous physical activity, sleep duration, alcohol, and fruit and vegetable consumption, as well as incidence of cardiometabolic diseases, and indicators of area-level disadvantage and rurality. Data was analysed in 2020. Higher dementia risks (albeit with imprecision) were found among participants who were underweight (Incidence Hazard Ratio (IHR) 1.30, 95%CI=0.86–1.86) and lower risks among those who were overweight (IHR=0.78, 95%CI=0.70–0.86) or obese (IHR=0.72, 95%CI=0.62–0.83) compared with ‘normal’ BMI. A ≥0.8 kg/m2 reduction in BMI associated with IHR=1.81 (95%CI=1.64–2.01) higher dementia risk relative to those with stable BMI. Higher dementia risk with decreasing BMI was fairly consistent relative to baseline BMI category. Adherence to physical activity and sleep duration guidelines were associated with reduced dementia risk, but neither these, nor adjustment for other behaviours and local factors, explained the BMI-dementia association. In conclusion, we replicated the BMI-dementia findings from a recent meta-analysis and provide further support to preventive strategies focussed on increasing physical activity and improving sleep duration. Other potential environmental risk factors outside of socioeconomic and urban/rural circumstances warrant investigation.

Weight change in middle adulthood and risk of cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort.

Obesity is a risk factor for several major cancers. Associations of weight change in middle adulthood with cancer risk, however, are less clear. We examined the association of change in weight and body mass index (BMI) category during middle adulthood with 42 cancers, using multivariable Cox proportional hazards models in the European Prospective Investigation into Cancer and Nutrition cohort. Of 241 323 participants (31% men), 20% lost and 32% gained weight (>0.4 to 5.0 kg/year) during 6.9 years (average). During 8.0 years of follow-up after the second weight assessment, 20 960 incident cancers were ascertained. Independent of baseline BMI, weight gain (per one kg/year increment) was positively associated with cancer of the corpus uteri (hazard ratio [HR] = 1.14; 95% confidence interval: 1.05-1.23). Compared to stable weight (±0.4 kg/year), weight gain (>0.4 to 5.0 kg/year) was positively associated with cancers of the gallbladder and bile ducts (HR = 1.41; 1.01-1.96), postmenopausal breast (HR = 1.08; 1.00-1.16) and thyroid (HR = 1.40; 1.04-1.90). Compared to maintaining normal weight, maintaining overweight or obese BMI (World Health Organisation categories) was positively associated with most obesity-related cancers. Compared to maintaining the baseline BMI category, weight gain to a higher BMI category was positively associated with cancers of the postmenopausal breast (HR = 1.19; 1.06-1.33), ovary (HR = 1.40; 1.04-1.91), corpus uteri (HR = 1.42; 1.06-1.91), kidney (HR = 1.80; 1.20-2.68) and pancreas in men (HR = 1.81; 1.11-2.95). Losing weight to a lower BMI category, however, was inversely associated with cancers of the corpus uteri (HR = 0.40; 0.23-0.69) and colon (HR = 0.69; 0.52-0.92). Our findings support avoiding weight gain and encouraging weight loss in middle adulthood.

Baseline prognostic nutritional index and changes in pretreatment body mass index associate with immunotherapy response in patients with advanced cancer

BackgroundRecent research suggests that baseline body mass index (BMI) is associated with response to immunotherapy. In this study, we test the hypothesis that worsening nutritional status prior to the start...

Traffic-related Air Pollution and Incident Obesity during Ages 10-18 years in the Southern California Children’s Health Study

Childhood obesity is a global public health crisis, often continuing into adulthood and contributing to increased morbidity and mortality. A growing literature suggests traffic pollution may contribute to increased BMI in childhood, but few studies have examined whether this translates to an increased risk of obesity. In this study we evaluated how traffic-related air pollution relates to incident obesity in a prospective study of schoolchildren from ages 10 to 18 years.The study population comprised 3430 children from eight Southern California communities who were not obese at study entry, recruited over three waves in 1992-93, 1995-96, and 2002-03. Children were followed until age 18 or high school graduation, and height and weight measurements were collected longitudinally. Residential traffic pollution exposure at baseline was estimated as nitrogen oxides (NOx) using the California line-source dispersion model. Multilevel Poisson regression models were fitted to estimate incidence rate ratios (IRR) for obesity associated with traffic-related NOx exposure, adjusting for a set of confounding variables selected a priori using a directed acyclic graph.Participants were primarily non-Hispanic White (44%) or Hispanic (40%). At study entry the median age was 9.7 (IQR: 9.3-10.1) and most children were of normal weight (78%). Traffic-related NOx was associated with increased risk of childhood obesity: IRR=1.10 (1.01-1.19) per average standard deviation within community. Further adjustment for baseline body mass index category increased the risk: IRR=1.14 (1.05-1.24).Exposure to traffic was associated with higher obesity risk in childhood. These findings strengthen the scientific evidence linking childhood obesity and air pollution from near-roadway sources, a modifiable risk factor which could be targeted through vehicular emissions reductions and exposure policies.

Differential Benefit of Adjuvant Docetaxel-Based Chemotherapy in Patients With Early Breast Cancer According to Baseline Body Mass Index.

Lipophilic drugs, such as taxanes, have a high affinity for adipose tissue and a resulting higher volume of distribution. Here, we reanalyzed clinical trial data to investigate whether the efficacy of docetaxel-based chemotherapy differs from non-docetaxel-based chemotherapy in patients with breast cancer according to their baseline body mass index (BMI). We retrospectively analyzed data from all of the patients in the adjuvant BIG 2-98 trial (ClinicalTrials.gov identifier: NCT00174655; N = 2,887) comparing non-docetaxel- to docetaxel-containing chemotherapy. BMI (kg/m2) was categorized as follows: 18.5 to < 25, lean; 25 to < 30, overweight; and ≥ 30, obese. Disease-free survival (DFS) was the primary endpoint, and overall survival (OS) was the secondary endpoint. A second-order interaction was assessed among treatment, BMI, and estrogen receptor (ER) status. There was no difference in DFS or OS according to BMI in the non-docetaxel group, while reduced DFS and OS were observed with increasing BMI category in the docetaxel group. Adjusted hazard ratios for DFS and OS were, respectively, 1.12 (95% CI, 0.98 to 1.50; P = .21) and 1.27 (95% CI, 1.01 to 1.60; P = .04) for overweight versus lean groups and were 1.32 (95% CI, 1.08 to 1.62; P = .007) and 1.63 (95% CI, 1.27 to 2.09; P < .001), respectively, for obese versus lean groups. Similar results were obtained when considering ER-negative and ER-positive tumors separately and when considering only patients who received a relative dose intensity ≥ 85% for docetaxel. A joint modifying role of BMI and ER status on treatment effect was evident for DFS (adjusted P = .06) and OS (adjusted P = .04). This retrospective analysis of a large adjuvant trial highlights a differential response to docetaxel according to BMI, which calls for a body composition-based re-evaluation of the risk-benefit ratio of the use of taxanes in breast cancer. These results now must be confirmed in additional series.

The health outcomes of inflammation and obesity in patients with heart failure

BackgroundAlthough obesity is a risk factor for cardiovascular disease, higher body mass index is related to longer event-free survival in patients with heart failure (HF). While previous research demonstrated that higher levels of inflammatory mediators were associated with shorter event-free survival, the effect of inflammation on the association between obesity and outcomes of HF have not been considered. HypothesisBased on the obesity paradox, we hypothesized that patients with higher baseline body mass index (BMI) would experience better event-free survival than those with lower BMI regardless of inflammatory status. MethodA sample of 415 patients with HF (age 61 ± 11.5 years; 31% female) provided blood to measure soluble tumor necrosis factor receptor1 (sTNFR1), a biomarker of inflammation. Patients were divided into 4 groups based on BMI and a median split of sTNFR1 levels: (1) high BMI ≥ 30 and sTNFR1 > 1804 pg/ml, (2) high BMI ≥ 30 and low sTNFR1 ≤ 1804 pg/ml, and (3) low BMI < 30 and high sTNFR1 > 1804 pg/ml vs. (4) low BMI < 30 and sTNFR1 ≤ 1804 pg/ml. Patients were followed for an average of 365 days to determine the time to first event of either all-cause hospitalization or death. ResultsThere were 177 patients (43%) who experienced either an all-cause hospitalization or death. In a Cox regression, high BMI and high sTNFR1 category predicted time to event (hazard ratio = 1.7, 95% confidence interval = 1.01–2.9) with age, gender, race, left ventricular ejection fraction, New York Heart Association functional class (I/II versus III/IV), log-transformed N-terminal Pro-B-type natriuretic peptide levels, prescribed statin (yes/no), and comorbidity as covariates. ConclusionBeing in a higher inflammation group was associated with shorter event-free survival regardless of BMI. This study provides evidence that inflammation is an important consideration in the association between obesity and better outcomes in patients with HF.

0681 Comparison Of Upper Airway Stimulation Outcomes Between Regions And Bmi Groups From The Adhere Registry

Abstract Introduction As factors influencing Upper Airway Stimulation (UAS) effectiveness in obstructive sleep apnea (OSA) patients are of interest, we compared changes in apnea hypopnea index (AHI) and Epworth Sleepiness Scale (ESS) based on region and baseline body mass index (BMI). Methods Patients (15≥AHI≤65) of the ADHERE registry with AHI at one-year were grouped by region (Europe (EU) vs United States (US)), and BMI (≤32kg/m2 vs 32-35kg/m2). T-tests and equivalence testing (if the former non-significant) was performed using two-one-sided t-tests. Equivalence margin for AHI was set between -5 and 5 and -2 and 2 for ESS. Results By December 2019, 553 of 1600 patients completed 1-year follow-up. Average age was 60±11, 75% male, BMI 29±4 kg/m2, ESS=11±6. Median AHI decreased from 33 to 10, median ESS decreased from 11 to 6. Response defined by 50% AHI reduction and &amp;lt;20 was 70%. Both regions had similar improvements in median AHI (EU: 33 to 10, US: 34 to 10, p &amp;lt; 0.001 vs baseline), median ESS (EU: 12 to 7; US: 11 to 6, p&amp;lt;0.001 vs baseline), and treatment response (EU: 71%, US: 68%). The mean AHI and ESS difference between regions met the equivalence margin. (AHI: mean difference: 0.34, CI:-1.78, 2.46, ESS: mean difference: 0.57, CI:-0.04, 1.19). Mean change in AHI at 1-year was equivalent in BMI groups (≤32 kg/m2 vs 32-35 kg/m2 respectively) median difference: -19.6 vs. -18.8; mean difference: -0.48, (CI:-3.95, 2.97) However, treatment response ratio was different; 73% vs. 60%, p=0.02, i.e. higher BMI patients were less likely to achieve AHI &amp;lt; 20. ESS scores were equivalent; median: 6 vs. 7; mean difference: -0.33, CI: [-1.16, 0.47]. Conclusion UAS influence on OSA severity defined by AHI and sleepiness was similar irrespective of region and BMI category, however, treatment response defined by 50% AHI reduction and &amp;lt;20 was greater in those with lower BMI. Support The statistical support was provided by Inspire Medical System.

The Impact of BMI Categories on Metabolic Abnormality Development in Chinese Adults Who are Metabolically Healthy: A 7-Year Prospective Study.

PurposeTo determine what metabolic abnormalities develop frequently among metabolically healthy adults over time according to different baseline body mass index (BMI) categories.Patients and MethodsA prospective cohort study was performed on 10,805 adults, who were metabolically healthy at the time of the 2008 survey. Participants were divided into four groups: metabolically healthy obese (MHO), metabolically healthy overweight (MHOW), metabolically healthy normal-weight (MHN), and metabolically healthy underweight (MHU). Modified Poisson regression models were used to evaluate the relationship of BMI with the development of metabolic abnormalities. Association rule mining was used to identify the most frequent abnormalities that developed over time.ResultsCompared with the MHN group, the adjusted relative risks of the MHO group were 1.57 (95% CI: 1.09–2.27) and 2.08 (95% CI: 1.59–2.73) for developing elevated fasting glucose and elevated blood pressure, respectively, after adjusting for lifestyle behaviours and dietary factors. At the end of follow-up, 33 (19.1%) MHO subjects and 342 (16.6%) MHOW subjects had elevated blood pressure as the predominant metabolic syndrome component, whereas 236 (9.0%) MHU subjects had elevated plasma glucose. The results were similar after stratification by sex.ConclusionMHO and MHOW subjects developed elevated blood pressure most frequently, and MHU subjects developed elevated blood glucose most commonly, regardless of sex.

Association of the Intensive Lifestyle Intervention With Total Knee Replacement in the Look AHEAD (Action for Health in Diabetes) Clinical Trial

BackgroundEvidence has established obesity as a risk factor for total knee replacement (TKR) due to osteoarthritis. Obesity is a risk factor for TKR. Randomized trials such as Look AHEAD (Action for Health in Diabetes) have shown long-term successful weight loss with an intensive lifestyle intervention (ILI). It is unknown, however, if intentional weight loss can reduce the risk of TKR. MethodsLook AHEAD randomized persons aged 45-76 with type 2 diabetes who had overweight or obesity to either an ILI to achieve/maintain 7% weight loss or to standard diabetes support and education (DSE). Reported knee pain was assessed using the Visual Analog Scale and Western Ontario McMaster University Osteoarthritis Index questionnaire in 5125 participants without previous TKR. Cox proportional hazard regression was used to model differences in risk of TKR in relation to randomization group assignment (ILI vs DSE) along with baseline body mass index category and baseline knee pain as potential confounders from baseline through Look AHEAD-Extension. ResultsBaseline mean ± SD Western Ontario McMaster University Osteoarthritis Index knee pain scores did not differ by treatment assignment (ILI: 3.6 ± 2.9, DSE: 3.9 ± 3.0, P = .08); as expected due to randomization. During follow up, the 631 (12%) participants who reported having a TKR were more likely to have been heavier (P < .001) and older (P < .001) at enrollment, but risk of TKR did not differ by treatment group assignment (hazard ratio [HR] 1.07, 95% confidence interval [CI] 0.91-1.25, P = .43). Heterogeneity of treatment effect was observed according to baseline knee pain (interaction P = .02). In persons without knee pain at baseline, there was a 29% reduced risk of TKR in ILI compared to DSE (HR 0.71, 95% CI 0.52-0.96). However, in persons with knee pain at baseline, there was no statistically significant association of treatment assignment with respect to subsequent TKR incidence (HR 1.11, 95% CI 0.92-1.33). ConclusionFindings suggest that intensive lifestyle change including physical activity, dietary restriction and behavioral changes to achieve weight loss for prevention of TKR may be most effective in preventing TKR prior to the development of knee pain.

Trace Proteinuria and the Incidence of Overt Proteinuria After Five Years: Results of the Kanagawa Investigation of the Total Checkup Data From the National Database-5 (KITCHEN-5).

BackgroundTrace proteinuria (TrP), which is usually defined as ± by dipstick urinalysis, is considered as normal and of limited clinical significance. However, the relationship between TrP and overt proteinuria (OP) (≥ +1) in the future is unknown. Therefore, we investigated the association between TrP and future incidence of OP in a community-based cohort study.MethodsTrP detected during the initial 2 years, which was classified into transient TrP (once/2 years) (T-TrP) and recurrent TrP (twice/2 years) (R-TrP); and the incidence of OP after 5 years were investigated in 292,257 general Japanese people aged 40 - 68 years who attended checkups. To determine TrP and OP, dipstick urinalysis was conducted with visual reading (VR) by medical staff or automated reading (AR) using a machine reader.ResultsOverall, T-TrP and R-TrP were observed in 24,782 (8.5%) and 3,767 (1.3%) subjects, respectively. Both types of TrP were prevalent in the detection with AR than VR. The prevalences of T-TrP and R-TrP showed J-shaped relationships against baseline body mass index (BMI), regardless of sex and BMI categories. The incident of OP after 5 years was larger (around 10%) in R-TrP than T-TrP (around 5%): approximately two times. Logistic regression analysis showed that T-TrP and R-TrP were significantly associated with OP, even after adjustment for relevant confounding factors including age, sex, and BMI (odds ratios (95% confidence intervals (CIs)): 2.77 (2.60 - 2.95) and 4.85 (4.34 - 5.43)), which were not largely altered when sub-analysis was conducted according to men and women, non-obesity and obesity, or AR and VR. In all analysis above, the odds ratios (95% CIs) of R-TrP for OP were higher than T-TrP.ConclusionsOur findings suggest that TrP, particularly R-TrP, is substantially associated with the future incidence of OP, which may be independent of confounding factors and the methods detecting TrP.