Weight Management in Adults With Obesity: What Is a Primary Care Clinician to Do?

Approach to Obesity Treatment in Primary Care: A Review

Importance

More than 40% of US adults have obesity, which increases the risks for multiple chronic diseases and premature mortality. Historically, nonsurgical interventions often have not led to sufficient weight loss and maintenance to improve health, but highly effective antiobesity medications (AOMs) have recently become available, and additional effective therapeutics are under development. Given that most medical care for adults with obesity is delivered in primary care settings, guidance for integrating weight-management approaches is needed.

Observations

Lifestyle interventions can lead to a mean weight loss of 2% to 9% of initial weight at 1 year and increase the likelihood of weight loss of 5% or more, but weight regain over time is common even with continued treatment. Adjunctive treatments, including AOMs and surgical approaches, can lead to larger, more sustained weight loss and improvements in numerous obesity-associated medical conditions. Highly effective AOMs, including nutrient-stimulated hormone-based therapies, induce mean weight loss of 15% or more. Barriers to intervention, including access to care, have a disproportionate influence on populations most affected by obesity and its consequences.

Conclusions and Relevance

Primary care clinicians play a vital role in the assessment, management, and support of patients with obesity. With careful clinical assessment and shared decision-making, a flexible treatment plan can be developed that reflects evidence of treatment efficacy, patient preference, and feasibility of implementation. Adjunctive therapies to lifestyle interventions, including more effective pharmacotherapeutics for obesity, offer hope to patients and the potential for considerable improvements in health and quality of life.

Patients eligible and referred for bariatric surgery in southeastern Ontario: Retrospective cohort study

OBJECTIVE

To evaluate the proportion of eligible individuals, within one health region in Ontario, who were referred for publicly funded medical and surgical weight-loss interventions (MSWLI).

DESIGN

A retrospective cohort study that used primary care data from the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) and referral data from the Ontario Bariatric Network (OBN).

SETTING

Primary care practices within southeastern Ontario that contribute data to CPCSSN.

PARTICIPANTS

Patients with class II (body mass index [BMI] 35.0 to 39.9 kg/m²) or III (BMI ≥ 40 kg/m²) obesity who were eligible for referral to the OBN for MSWLI.

MAIN OUTCOME MEASURES

Primary care data about patients within the CPCSSN database were linked to referral records within the OBN database using 3 indirect identifiers to determine the proportion of patients with class II and III obesity who were referred to the OBN for MSWLI. An adjusted multivariate logistic regression model was used to determine the most significant predictors of referral.

RESULTS

Of the 87 276 patients within one health region in Ontario, 15 526 (17.8%) patients had class II or III obesity and were eligible for referral for MSWLI. Only 966 out of those 15 526 (6.2%) patients were actually referred for MSWLI. In the multivariate regression analysis, BMI had the strongest association with referral in terms of adjusted odds ratio (AOR), varying from 2.50 (95% CI 2.04 to 3.06) for a BMI of 40.0 to 44.9 kg/m², to 5.15 (95% CI 4.21 to 6.30) for a BMI of 50.0 kg/m² or greater. Referral was more likely for female than male patients (AOR = 2.18; 95% CI 1.86 to 2.57), those living rurally than for urban dwellers (AOR = 1.39; 95% CI 1.20 to 1.60), and those aged 30 to 39 (AOR = 1.61; 95% CI 1.24 to 2.09) and 40 to 49 (AOR = 1.53; 95% CI 1.18 to 1.98) compared with other age groups.

CONCLUSION

Within one health region in Ontario, the referral rate of patients with class II and III obesity for MSWLI was low. Our findings highlight the need for further research to understand and address the barriers to referral of patients with class II and III obesity for MSWLI.

Association of Weight Loss With Type 2 Diabetes Remission Among Adults in Medically Underserved Areas: A Retrospective Cohort Study

PURPOSE

To examine the association between weight loss and type 2 diabetes remission among vulnerable populations living in medically underserved areas of the Mid-Southern United States.

DESIGN

Quantitative, retrospective cohort study.

SETTING

114 ambulatory sites and 5 adults' hospitals in the Mid-South participating in a regional diabetes registry.

PARTICIPANTS

9,900 adult patients with type 2 diabetes, stratified by remission status, with 1 year of baseline electronic medical record data, and 1 year of follow-up data for the 2015-2018 study period.

MEASURES

The outcomes were diabetes remissions, categorized as any remission, partial remission, and complete remission based on the guidelines of the American Diabetes Association. The exposure was weight loss, calculated by the change in the Body Mass Index (BMI) as a proxy measure.

ANALYSIS

χ² tests, Fisher's exact tests, and the Mann-Whitney U-test were used to examine the differences in patient characteristics by remission status across the 3 remission categories, as appropriate. Multiple multivariable logistic regressions adjusting for confounders were performed to estimate the adjusted odds ratios (aORs) for the associations between weight loss and diabetes remission.

RESULTS

Among 9,900 patients identified, a reduction of 0.3 kg/m² (standard deviation: 2.5) in the average BMI from the baseline to the follow-up was observed. 10.8% achieved any type of remission, with 9.8% for partial and 1.0% for complete remissions. Greater weight loss was significantly associated with an increased likelihood of any (aOR = 1.07, 95% confidence interval (CI), 1.06-1.08), partial (aOR 1.06, 95% CI, 1.04-1.07), and complete diabetes remission (aOR 1.10, 95% CI, 1.07-1.13).

CONCLUSIONS

Weight loss is significantly associated with diabetes remission among patients living in medically underserved areas, but complete remission is rare.

Clinical Implications for Women of a Low-Carbohydrate or Ketogenic Diet With Intermittent Fasting

Obesity in the United States is pervasive and associated with morbidity, mortality, and increased health care costs. For women, obesity may affect stages of life including early menarche, fertility, pregnancy, and menopause as a result of hormonal imbalances and insulin resistance. The insulin-carbohydrate model of obesity has been proposed as an explanation for growing obesity rates and can be used to target weight loss strategies by increasing insulin sensitivity. Together, low-carbohydrate dietary patterns along with intermittent fasting may help individuals with insulin resistance not only lose weight but also increase their insulin sensitivity. The purpose of this article is to review the epidemiology and physiology of obesity and the indicators for health while outlining strategies for nurses and other clinicians to use when counseling women who are following a low-carbohydrate or ketogenic diet with intermittent fasting for weight management.

A Methodologic Systematic Review of Mobile Health Behavior Change Randomized Trials

CONTEXT

Mobile health helps providers offer accessible, affordable, tailored behavior change interventions. However, research assessing mobile health interventions may feature methodologic shortcomings and poor reporting. This review aims to summarize the characteristics, methods, and intervention reporting of RCTs evaluating mobile health behavior change interventions.

EVIDENCE ACQUISITION

This was a methodologic systematic review of RCTs assessing mobile health behavior change interventions published in PubMed from January 1, 2014 to January 1, 2018, in journals with the upper half of Impact Factors (Clarivate Analytics). Three reviewers independently extracted sample characteristics. Primary outcomes were classified as patient-important or not using definitions from the literature. Any non-patient-important outcomes were then reclassified by a panel of 3 patients. Intervention reporting was assessed by the mobile health Evidence Reporting and Assessment checklist. Data were analyzed in December 2018.

EVIDENCE SYNTHESIS

Most of the 231 included RCTs assessed text messaging (51%) or smartphone app (28%) interventions aiming to change nutrition and physical activity (36%) or treatment adherence (25%). Only 8% of RCTs had a patient-important primary outcome, follow-up of ≥6 months, and intent-to-treat analysis. Most primary outcomes were behavioral measures (60%). Follow-up was <3 months in 29% of RCTs. Regarding reporting, 12 of the 16 checklist items were reported in less than half of RCTs (e.g., usability/content testing, 32%; data security, 13%).

CONCLUSIONS

Reports of RCTs assessing mobile health behavior change interventions lack information that would be useful for providers, including reporting of long-term intervention impact on patient-important primary outcomes and information needed for intervention replicability.