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Impact of Sustained Weight Loss on Cardiometabolic Outcomes

Open AccessPublished:October 24, 2021DOI:https://doi.org/10.1016/j.amjcard.2021.09.018

      Highlights

      • Sustained weight loss significantly lowers incidence of cardiometabolic outcomes.
      • Sustained weight loss significantly delays onset of cardiometabolic outcomes.
      • Greater weight loss significantly delays onset of cardiometabolic outcomes.
      Obesity increases the risk of developing type 2 diabetes, hypertension, and hyperlipidemia. We sought to determine the impact of obesity maintenance, weight regain, weight loss maintenance, and magnitudes of weight loss on future risk and time to developing these cardiometabolic conditions. This was a retrospective cohort study of adults receiving primary care at Geisinger Health System between 2001 and 2017. Using electronic health records, patients with ≥3-weight measurements over a 2-year index period were identified and categorized. Obesity maintainers (OM) had obesity (body mass index ≥30 kg/m²) and maintained their weight within ±3% from baseline (reference group). Both weight loss rebounders (WLR) and weight loss maintainers (WLM) had obesity at baseline and lost >5% body weight in year 1; WLR regained ≥20% of weight loss by end of year 2 and WLM maintained ≥80% of weight loss. Incident type 2 diabetes, hypertension, and hyperlipidemia, and time-to-outcome were determined for each study group and by weight loss category for WLM. Of the 63,567 patients included, 67% were OM, 19% were WLR, and 14% were WLM. The mean duration of follow-up was 6.6 years (SD, 3.9). Time until the development of electronic health record-documented type 2 diabetes, hypertension, and hyperlipidemia was longest for WLM and shortest for OM (log-rank test p <0.0001). WLM had the lowest incident type 2 diabetes (adjusted hazard ratio [HR] 0.676 [95% confidence interval [CI] 0.617 to 0.740]; p <0.0001), hypertension (adjusted HR 0.723 [95% CI 0.655 to 0.799]; p <0.0001), and hyperlipidemia (adjusted HR 0.864 [95% CI 0.803 to 0.929]; p <0.0001). WLM with the greatest weight loss (>15%) had a longer time to develop any of the outcomes compared with those with the least amount of weight loss (<7%) (p <0.0001). In an integrated delivery network population, sustained weight loss was associated with a delayed onset of cardiometabolic diseases, particularly with a greater magnitude of weight loss.
      The prevalence of obesity has risen dramatically in the United States; per the 2017 to 2018 National Health and Nutrition Examination Survey, 42.4% of US adults have obesity.
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      Managing obesity is a lifelong endeavor as there are many biological, social, psychological, and environmental factors contributing to weight gain and loss.
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      ,
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      Modest weight loss of at least 5% is clinically beneficial
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      and recommended by clinical treatment guidelines,
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      which can be achieved with various clinical and behavioral treatment options. However, long-term weight loss maintenance remains challenging owing to the biology of obesity, hence weight regain is common;
      • Elfhag K
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      Long-term weight loss maintenance.
      about 80% of the weight loss is regained within 5 years.
      • Hall KD
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      Maintenance of lost weight and long-term management of obesity.
      Clinical outcomes of lifestyle, behavioral, and clinical treatment interventions have been examined,
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      but limitations include the relatively short duration of follow-up observations; additionally, there is scant literature describing clinical outcomes of sustained weight loss in real-world settings. This study aims to evaluate the long-term impact of obesity, weight loss with regain, and weight loss maintenance, with the latter explored across varying weight loss thresholds. This research seeks to understand the relation between long-term weight maintenance and clinical relevance to 3 cardiometabolic outcomes: type 2 diabetes, hypertension, and hyperlipidemia in a large integrated delivery network setting.

      Methods

      This is a retrospective observational study of patients receiving primary care between 2001 and 2017 at Geisinger Health System, a Pennsylvania-based integrated delivery network that includes a health plan, acute care hospitals, specialty hospitals, ambulatory surgery centers, and clinical services such as the Center for Nutrition and Weight Management.
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      Continuous innovation in health care: implications of the Geisinger experience.
      ,

      Geisinger research units. Available at: https://www.geisinger.edu/research/departments-and-centers/obesity-institute. Accessed September 21, 2020.

      Geisinger Health System is 1 of the largest healthcare organizations in the United States and serves over 3 million residents including employees, individuals/families, and adults aged 65 and older. The Geisinger Institutional Review Board reviewed the study and determined that the research does not involve human subjects, thus deeming it exempt from Institutional Board oversight (IRB #: 2019-0138). Data were extracted from the Epic electronic health record (EHR) system in several stages to efficiently capture eligible subjects and define and analyze study outcomes.
      The study population was limited to adult patients (age ≥18 years) with 3 or more EHR-documented weight measurements within 2 years, denoted as the index period; these measurements included a baseline weight, a 1-year weight (within 6 to 18 months), and a 2-year weight (within 12 to 24 months). The index period was set at 2 years to allow adequate time to discern clinically relevant weight change patterns. Patients who underwent bariatric surgery before or during the index period and patients with prevalent cancer or a history of cancer during the same time window were excluded from the study; for pregnant women, the weight measurements within 6 months of the pregnancy indicators were also excluded.
      The study sample was separated into 3 groups based on weight trends during each year of the index period: (1) obesity maintainers (OM), patients with a history of obesity who maintained weight within ±3% margin from baseline; (2) weight loss rebounders (WLRs), patients with a history of obesity who lost >5% weight via nonsurgical methods (i.e., pharmacotherapy and/or lifestyle intervention) and regained weight from baseline (defined as regaining ≥20% of 1-year weight loss
      • King WC
      • Hinerman AS
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      • Wahed AS
      • Courcoulas AP.
      Comparison of the performance of common measures of weight regain after bariatric surgery for association with clinical outcomes.
      ); and (3) weight loss maintainers (WLMs), patients with obesity at baseline who lost >5% weight via non-surgical methods and maintained weight loss from baseline (defined as maintaining ≥80% of 1-year weight loss). The WLM group was stratified by the amount of initial weight loss. Patients who did not meet the definition of the 3 groups were excluded from the analysis.
      Outcomes analyzed include type 2 diabetes mellitus, hypertension, and hyperlipidemia. The status of these conditions was defined by EHR documentation of International Classification of Diseases 10th edition (ICD-10) codes (or at least 2 outpatient visits) or treatment for the condition; for diabetes, the presence of a hemoglobin A1c level of >6.5% with diabetes medication treatment was also included to identify the relatively few patients who had a strong indication of diabetes despite the lack of a diagnosis code (Online Appendix 1). Diabetes, hypertension, and hyperlipidemia were classified as prevalent or incident based on the timing of meeting the diagnostic criteria—before or during the index period was considered prevalent, and after the index period was considered incident (Online Appendix 1). Additionally, A1c and systolic blood pressure (SBP) were also examined as outcomes related to diabetes and hypertension, respectively.
      EHR data on weight measurements, socio-demographics, vital signs, laboratory tests, encounters, procedures, diagnostic codes, orders (pharmacological, nutrition consults, diet, etc.) were extracted. The median height of a patient was calculated and used for all body mass index (BMI) measures (Online Appendix 1). Timing of weight measurements was determined to identify periods when patients had 3 EHR-recorded weight measurements over a 2 to 3-year period. All weight measurements during the first 15 months of participation in Geisinger primary care for each patient were excluded to provide a lead-in period to establish medical history. A baseline weight resulting in a BMI ≥30 kg/m² was used to define the beginning of the index period (considered time 0). A second weight measurement occurred approximately 12 months after baseline (within 6 to 18 months) and a third measurement occurred at least 12 months after the second (within 12 to 24 months of baseline). A follow-up visit occurred at least 6 months after the third weight measure. The median follow-up period between the baseline and 1-year weight measurement ranged from 365 to 366 days across the 3 study groups. Follow-up duration between baseline and 2-year weight was also similar for the 3 groups, ranging from a median of 787 to 798 days.
      Analyses evaluated independent and joint associations of weight loss and weight maintenance on each clinical indicator: type 2 diabetes, hypertension, and hyperlipidemia, starting with descriptive statistics and unadjusted analysis, followed by adjusted regression modeling. The simple analyses evaluated the unadjusted association of each clinical indicator for the study groups (OM, WLR, and WLM) using Cox regression for dichotomous outcomes (i.e., time-to-event regression model). For each clinical indicator, time-to-outcome was calculated as the number of days between the initial baseline weight measurement until the outcome of interest happens. For patients who did not develop the outcome of interest, the time was censored at the last follow-up visit. Testing for proportional hazard assumptions allows for the examination of consistent effects in the short and long term. We used a repeatedmeasures linear model with a first-degree autoregressive covariance structure (SAS PROC MIXED). Model assumptions were validated using residual plots (e.g., QQ plots, residuals vs time, residuals vs predicted).
      Following the unadjusted analyses were models adjusting for selected patient characteristics and testing whether these characteristics modify the effect of weight loss on the clinical outcomes using the OM group as the reference group. The final models were adjusted for age, gender, BMI, diabetes, hypertension treatment, hyperlipidemia treatment, depression/anxiety treatment, osteoarthritis, asthma, gastrointestinal reflux disease, and the Charlson Comorbidity index. The Charlson Comorbidity Index is a validated score combining multiple comorbidities into a 10-year survival predictor.
      • Charlson ME
      • Pompei P
      • Ales KL
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      A new method of classifying prognostic comorbidity in longitudinal studies: development and validation.
      Comorbidities in this research were based on EHR diagnosis codes, weighted higher for diseases with greater mortality risk. Subgroup analyses were conducted for A1c among patients with prevalent diabetes and uncontrolled A1c (A1c ≥6.5%) and for SBP among those with prevalent hypertension and uncontrolled SBP (SBP ≥140 mm Hg); analyses were not conducted for lipid levels owing to limited availability of laboratory test data.
      The cumulative incidence of each outcome was estimated by the Kaplan-Meier method and plotted over 10 years of follow-up for each group. In addition, Kaplan-Meier curves were used to compare time until outcome within the WLM group stratifying by the amount of weight loss at the end of year 2 of the index period (<7%, 7% to 10%, >10% to 15%, and >15%) using <7% weight loss as the reference group. A minimum weight loss of 7% was examined based on research demonstrating the effect of weight loss of at least 7% on preventing or delaying the development of type 2 diabetes.
      • Knowler WC
      • Fowler SE
      • Hamman RF
      • Christophi CA
      • Hoffman HJ
      • Brenneman AT
      • Brown-Friday JO
      • Goldberg R
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      • Nathan DM.
      Diabetes Prevention Program Research Group
      10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study.
      ,
      • Knowler WC
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      Diabetes Prevention Program Research Group. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin.
      The analyses were conducted using SAS version 9.4 (SAS Institute Inc., Cary North Carolina).

      Results

      Of the study sample of 63,567 patients, the majority (67%) were classified as OM (reference group). The remaining sample was similarly distributed between WLR (19%) and WLM (14%). The mean follow-up was 6.6 years (SD = 3.9). Female and younger patients were significantly more likely than male and older patients, respectively, to lose weight at 1 year (p <0.0001 for both). Baseline descriptive statistics and disease status for the study population are listed in Table 1. Median weight loss from baseline to the 2-year weight measurement was 2.5% for the WLR group and 10.7% for the WLM group.
      Table 1Baseline descriptive statistics of study population
      VariableOM (n = 42,534)WLR (n = 12,227)WLM (n = 8,806)p Value
      Age (years)53.3 (14.5)47.9 (15.4)50.1 (17.2)<0.0001
      Baseline BMI (kg/m2)35.3 (5.4)35.9 (6.1)35.8 (6.2)<0.0001
      Women22,136 (52.0%)7,600 (62.2%)5,838 (66.3%)<0.0001
      White41,337 (97.2%)11,855 (97.0%)8,510 (96.7%)0.096
      Hispanic544 (1.3%)171 (1.4%)141 (1.6%)
      Black522 (1.2%)159 (1.3%)132 (1.5%)
      Asian59 (0.1%)21 (0.2%)9 (0.1%)
      Hawaiian26 (<0.1%)7 (<0.1%)1 (<0.1%)
      American Indian24 (<0.1%)9 (<0.1%)5 (<0.1%)
      Other/unknown22 (<0.1%)5 (<0.1%)8 (<0.1%)
      Type 2 diabetes mellitus7,175 (16.9%)1,709 (14.0%)1,648 (18.8%)<0.0001
      Prediabetes5,981 (14.1%)1,445 (11.8%)1,059 (12.0%)<0.0001
      Treatment for hyperlipidemia13,853 (32.6%)3,025 (24.7%)2,527 (28.7%)<0.0001
      Treatment for hypertension20,166 (47.4%)4,775 (39.1%)3,899 (44.3%)<0.0001
      Any cardiovascular disease10,007 (23.5%)2,516 (20.6%)2,252 (25.6%)<0.0001
      Congestive heart failure903 (2.1%)258 (2.1%)307 (3.5%)<0.0001
      Stroke57 (0.1%)20 (0.2%)22 (0.3%)0.042
      Myocardial infarction483 (1.1%)121 (1.0%)93 (1.1%)0.364
      Osteoarthritis8,107 (19.1%)2,141 (17.5%)1,813 (20.6%)<0.0001
      Treatment for depression/anxiety12,489 (29.4%)4,488 (36.7%)3,437 (39.0%)<0.0001
      Asthma4,118 (9.7%)1,484 (12.1%)1,089 (12.4%)<0.0001
      Gastroesophageal reflux disease (GERD)10,147 (23.9%)2,942 (24.1%)2,254 (25.6%)0.0023
      Charlson Index = 028,753 (67.6%)8,442 (69.0%)5,488 (62.3%)<0.0001
      Charlson Index = 110,177 (23.9%)2,757 (22.6%)2,229 (25.3%)
      Charlson Index = 2+3,604 (8.5%)1,028 (8.4%)1,089 (12.4%)
      Only conditions for which adjustments were made were included.
      BMI = body mass index; OM = obesity maintainer; WLM = weight loss maintainer; WLR = weight loss rebounder.
      Only a small percentage of patients had any evidence of weight-loss interventions including visits with a weight loss specialist, visits with a registered dietitian, or obesity medication treatment (i.e., phentermine, orlistat, or other treatments). Patients who lost weight (WLR and WLM) were more likely to have any of the 3 interventions; 4.5% of WLR and 3.9% of WLM had any weight loss treatment during the index period, compared with 2.5% of OM (p <0.0001).
      A total of 49,327 patients were included in this analysis (n = 33,260 OM, n = 9,630 WLR, and n = 6,437 WLM). Mean follow-up time for the 3 groups is listed in Online Table S1. Patients diagnosed with diabetes (type 1 and type 2) before baseline or during the index period were excluded from the analysis (n = 14,240 total; n = 9,274 OM, n = 2,597 WLR, and n = 2,369 WLM). WLM patients had the longest time until EHR-documented type 2 diabetes and OM patients had the shortest time (log-rank test p <0.0001; Figure 1). By 5 years, the incidence of type 2 diabetes in the study population was 11.1% for the OM group, 9.1% for WLR, and 6.5% for WLM, with a similar trend seen at 10 years of follow-up: 20.2% for the OM group, 17.9% for WLR, and 13.4% for WLM. Those in the WLM group had a 33% lower risk of future incident type 2 diabetes compared with those in the OM group (adjusted hazard ratio [HR] = 0.68; 95% confidence interval [CI] 0.62 to 0.74; p <0.0001); the difference between OM and WLR was not significant.
      Figure 1
      Figure 1Kaplan-Meier curves for time to develop cardiometabolic outcomes stratified by OM, WLM, and WLR. (A) (Top) Time to develop type 2 diabetes for OM, WLM, and WLR. (B) (Middle) Time to develop hypertension for OM, WLM, and WLR. (C) (Bottom) Time to develop hyperlipidemia for OM, Obesity Maintainer; WLM, Weight Loss Maintainer; WLR, Weight Loss Rebounder.
      Among the patients with prevalent diabetes and A1c ≥6.5% (n = 5,883), in repeated measures linear regression (accounting for correlation within patients that have sufficient data to provide multiple spans and changes from 1 study group to another), both the WLR and WLM groups had a lower A1c level during follow-up as compared with the OM group. WLR had a mean −0.26% lower A1c than OM and WLM had a mean −0.23% lower A1c (both p <0.0001; Figure 2).
      Figure 2
      Figure 2Adjusted mean A1c during follow-up for patients with prevalent diabetes and A1c ≥6.5 at baseline.
      A sample of 24,172 patients was included in the analysis (n = 15,330 OM, n = 5,358 WLR, and n = 3,484 WLM). Mean follow-up time for the 3 groups is listed in Online Table S2. Patients diagnosed with hypertension or who received hypertension treatment before baseline or during the index period were excluded from the analysis (n = 39,395 total; n = 27,204 OM, n = 3,869 WLR, and n = 5,322 WLM). Time to EHR-recorded hypertension was greatest for WLM and shortest for OM (log-rank test p <0.0001; Figure 1). After 5 years of follow-up, the incidence of hypertension was 18.9% for OM, 15.9% for WLR, and 11.7% for WLM. At 10 years, the incidence was 29.8%, 26.0%, and 20.1% for OM, WLR, and WLM, respectively. The WLM group had a 28% lower risk of developing hypertension compared with OM (adjusted HR = 0.72; 95% CI 0.66 to 0.80; p <0.0001). The difference between OM and WLR was not significant.
      In the 9,568 patients with prevalent hypertension (defined as treatment with a hypertension medication) and SBP ≥140 mm Hg, in repeated measures linear regression, both the WLR and WLM groups had lower SBP during follow-up as compared with the OM group. The WLR group had a mean 0.55 mm Hg lower SBP (p = 0.004) and the WLM group had a mean 2.81 mm Hg lower SBP, p <0.0001. Additionally, differences between WLR and WLM were significant (p <0.0001; Online Figure S1).
      A total of 27,473 patients in the study population were analyzed for hyperlipidemia (n = 17,268 OM, n = 6,058 WLR, and n = 4,147 WLM). Mean follow-up time for the 3 groups is listed in Online Table S3. Patients diagnosed with hyperlipidemia or who received treatment with a lipid medication before baseline or during the index period were excluded from the analysis (n = 36,094 total; n = 9,274 OM, n = 2,597 WLR, and n = 2,369 WLM). WLM experienced the longest time until treatment for hyperlipidemia and OM had the shortest time to treatment (log-rank test p <0.0001; Figure 1). After 5 years of follow-up, the incidence of hyperlipidemia was 23.5% for the OM group, 19.6% for WLR, and 16.8% for WLM, with the pattern continuing through 10 years. At the 10-year follow-up, the incidence was 40.8% for the OM group, 35.5% for WLR, and 30.7% for WLM. Compared with OM, the WLM group had a 14% lower risk of developing hyperlipidemia (adjusted HR = 0.86; 95% CI 0.80 to 0.93; p <0.0001). There was no significant difference between OM and WLR.
      Patients in the WLM group with the greatest weight loss (>15%) had a longer time developing any of the 3 cardiometabolic outcomes compared with those who had the least amount of weight loss (<7%) (p <0.0001; Figure 3); the adjusted HRs for the risk of developing each outcome are listed in Table 2. The risk of developing type 2 diabetes was lower for all 3weight loss thresholds compared with those with <7% weight loss. Patients with sustained weight loss >10% to 15% and >15% had a significantly lower risk of future incident hypertension as compared with those with <7% weight loss; those with the greatest amount of weight loss (>15%) had the lowest risk of developing hyperlipidemia.
      Figure 3
      Figure 3Kaplan-Meier curves for time to develop cardiometabolic outcomes within the WLM group stratified by the amount of weight loss at the end of the 2+ year index period. (A) (Top) Time to develop type 2 diabetes for the WLM group by amount of weight loss. (B) (Middle) Time to develop hypertension for the WLM group by amount of weight loss. (C) (Bottom) Time to develop hyperlipidemia for the WLM group by amount of weight loss. WL = weight loss WLM, Weight Loss Maintainer.
      Table 2Adjusted Cox regression model for risk of developing cardiometabolic conditions for Weight Loss Maintainer (WLM) group by amount of weight loss
      Outcome
      Models were adjusted for age, gender, BMI, Charlson Index, osteoarthritis, depression/anxiety treatment, hypertension treatment, hyperlipidemia treatment, diabetes, asthma, and gastroesophageal reflux disease (GERD). CI = confidence interval; HR = hazard ratio.
      Weight Loss ComparisonAdjusted HR95% CIp Value
      Type 2 diabetes (n = 6,437)7–10% versus <7%

      >10–15% versus <7%

      >15% versus <7%
      0.77

      0.67

      0.46
      [0.62 to 0.97]

      [0.53 to 0.85]

      [0.34 to 0.62]
      0.028

      0.0007

      <0.0001
      Hypertension (n = 3,484)7–10% versus <7%

      >10–15% versus <7%

      >15% versus <7%
      0.92

      0.65

      0.63
      [0.71 to 1.20]

      [0.50 to 0.85]

      [0.47 to 0.85]
      0.544

      0.0015

      0.0025
      Hyperlipidemia (4,147)7–10% versus <7%

      >10–15% versus <7%

      >15% versus <7%
      0.93

      0.85

      0.75
      [0.76 to 1.13]

      [0.70 to 1.03]

      [0.61 to 0.93]
      0.449

      0.088

      0.0090
      low asterisk Models were adjusted for age, gender, BMI, Charlson Index, osteoarthritis, depression/anxiety treatment, hypertension treatment, hyperlipidemia treatment, diabetes, asthma, and gastroesophageal reflux disease (GERD).CI = confidence interval; HR = hazard ratio.
      Patients in the type 2 diabetes analysis and those included in the hypertension analysis were stratified by the amount of weight loss in the WLM group. In repeated measures linear regression, higher amounts of sustained weight were associated with larger decreases in A1c. Compared with patients with <7% weight loss, those with >10% to 15% weight loss had a mean −0.24% lower A1c and those with >15% weight loss had a mean −0.23% lower A1c (both p <0.0001). The majority of the effect was observed in the first 3 years of follow-up. In the first year following the index period, a greater magnitude of weight loss was associated with a decrease in SBP (for each 1% increase in weight loss the mean SBP was 0.32-mm Hg lower, p = 0.001).

      Discussion

      This study joins the growing body of research illustrating the important role of the electronic medical record in outcomes research in various disease states.
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      This research demonstrates that sustained weight loss is associated with a reduced risk of developing type 2 diabetes, hypertension, and hyperlipidemia; it is also associated with a longer time until onset. The impact was greatest in the WLM patients who had the greatest magnitude of weight loss. Compared with patients who had <7% weight loss, those with more than 7% weight loss had a significantly lower risk of future incident type 2 diabetes, and those with 10% weight loss had a significantly lower risk of hypertension; significant risk reduction for hyperlipidemia was only seen with the greatest weight loss (>15%). Weight loss, regardless of being sustained over time, was associated with lower A1c levels in patients with prevalent diabetes; however, higher amounts (more than 10% weight loss in the WLM group) of sustained weight were associated with larger decreases in A1c. All study groups, including OM, had large reductions in SBP from baseline to 1 year after the index period, and the magnitude of SBP decrease was statistically significantly associated with weight loss. After the initial drop in SBP, all groups appear to have comparable decreases in SBP over time, suggesting that changes in SBP after year 1 of follow-up were not caused by the weight change in prior years, which seems reasonable given the susceptibility of SBP to localized temporal changes.
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      • Fowler CE
      • Nay CK
      • Miller NM
      • Burant CF
      • Herman WH.
      Impact of weight loss on waist circumference and the components of the metabolic syndrome.
      Although weight loss was much less common than obesity maintenance in our study, the findings also suggest that clinically meaningful weight loss, favorably affecting the incidence and severity of obesity-related disease, is occurring despite the documented limitations in comprehensive obesity care among primary care providers including lack of obesity care reimbursement and obesity treatment guideline knowledge.
      • Gomez G
      • Stanford FC.
      US health policy and prescription drug coverage of FDA-approved medications for the treatment of obesity.
      • Jannah N
      • Hild J
      • Gallagher C
      • Dietz W.
      Coverage for obesity prevention and treatment services: analysis of Medicaid and state employee health insurance programs.
      • Bertakis KD
      • Azari R.
      The impact of obesity on primary care visits.
      • Ciciurkaite G
      • Moloney ME
      • Brown RL.
      The incomplete medicalization of obesity: physician office visits, diagnoses, and treatments, 1996–2014.
      • Phelan SM
      • Burgess DJ
      • Yeazel MW
      • Hellerstedt WL
      • Griffin JM
      • van Ryn M.
      Impact of weight bias and stigma on quality of care and outcomes for patients with obesity.
      • Turner M
      • Jannah N
      • Kahan S
      • Gallagher C
      • Dietz W.
      Current knowledge of obesity treatment guidelines by health care professionals.
      Lastly, this study provides an important opportunity for improved collaborative care between primary care physicians and weight management specialists to increase the percentage of patients who maintain weight loss, and the magnitude of that weight loss.
      There are some limitations to this research. Owing to the retrospective nature of the study, there is some missing or unknown information often because of lack of clinical suspicion or need to collect the information. When defining outcomes of interest, multiple signals were reviewed to reduce misclassification (e.g., for diabetes and hyperlipidemia, we reviewed multiple sources of diagnoses, medication use, and lab results). Furthermore, the outcome definition used in this study (ICD-10 and treatment) may be a limiting factor, as it is likely that there are patients who have diabetes, hypertension, and/or hyperlipidemia based on objective laboratory value but no ICD diagnosis and are not receiving treatment.
      Weight measurements recorded within the index period varied based on available data in the EMR; this variability was minimized by selecting the measurements closest to the 1-year and to the 2-year time period. The index period was the only time during which weight was monitored; weight changes occurring after the index period were not documented and may have affected the analyzed outcomes. Additionally, there are possible effects of regression to the mean in the WLR group.
      The models were adjusted for selected patient characteristics such as baseline weight loss treatment types, age, gender, and BMI, but there could be a potential for confounding for variables that were not tested. The generalizability of the study findings may be limited owing to the racial and ethnic make-up of the study population. However, our results may be conservative due to the higher prevalence of obesity and cardiometabolic conditions in minority populations.
      Additionally, there was a lack of information about how weight loss was achieved during the period when patients were assigned to 1 of 3 groups or whether it was intentional. Given that patients with bariatric surgery and active cancer were excluded and that <5% received any weight loss treatment (e.g., visits with a weight loss specialist or registered dietitian, or pharmacology), we are left with the assumption that patients pursued care independent of their primary care provider, perhaps through a commercial program, worksite health program, lifestyle management, or another strategy. The very small portion of the study population receiving clinical treatment for obesity is consistent with the literature.
      In a large, integrated delivery network-based population retrospectively evaluated over 10 years, weight loss and sustained weight loss were associated with delayed onset of cardiometabolic diseases and improved outcomes. These associations are enhanced with greater magnitudes of weight loss.

      Disclosures

      Abhilasha Ramasamy, Neeraj N. Iyer, and B. Gabriel Smolarz are employed by Novo Nordisk, Inc., which sponsored this research. At the time this study was conducted, Neela Kumar was an employee of Novo Nordisk, Inc. Lisa Bailey-Davis, G. Craig Wood, Peter Benotti, Adam Cook, James Dove, Jacob Mowery, and Christopher Still are employed by Geisinger Health, which received funding from Novo Nordisk, Inc. for work performed on this study.

      Acknowledgment

      Writing assistance was provided by Rebecca Hahn, MPH of KJT Group, Inc. and funded by Novo Nordisk, Inc. Samantha M.R. Kling, PhD, contributed to the study design before completing a postdoctoral fellowship at Geisinger Health.

      Ethics Approval

      The Geisinger Institutional Review Board reviewed the study, determined it qualified for exempt status, and granted a waiver of patient consent (IRB #: 2019-0138).

      Data Availability

      No data are available. None of the participant (de-identified) data collected in the study can be shared.

      Appendix. Supplementary materials

      • Online Figure S1. Adjusted mean systolic blood pressure (SBP) during follow-up for patients with prevalent hypertension and SBP ≥140 at baseline. OM = obesity maintainer; SBP = systolic blood pressure; WLM = weight loss maintainer; WLR = weight loss rebounder.

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