As the prevalence of obesity increases, rationing arthritis care is not the answer

Covariate dependent Markov chains constructed with gradient boost modeling can effectively generate long-term predictions of obesity trends

IMPORTANCE

The prevalence of obesity among United States adults has increased from 30.5% in 1999 to 41.9% in 2020. However, despite the recognition of long-term weight gain as an important public health issue, there is a paucity of studies studying the long-term weight gain and building models for long-term projection.

METHODS

A retrospective, cross-sectional cohort study using the publicly available National Health and Nutrition Examination Survey (NHANES 2017-2020) was conducted in patients who completed the weight questionnaire and had accurate data for both weight at time of survey and weight ten years ago. Multistate gradient boost modeling classifiers were used to generate covariate dependent transition matrices and Markov chains were utilized for multistate modeling.

RESULTS

Of the 6146 patients that met the inclusion criteria, 3024 (49%) of patients were male and 3122 (51%) of patients were female. There were 2252 (37%) White patients, 1257 (20%) Hispanic patients, 1636 (37%) Black patients, and 739 (12%) Asian patients. The average BMI was 30.16 (SD = 7.15), the average weight was 83.67 kilos (SD = 22.04), and the average weight change was a 3.27 kg (SD = 14.97) increase in body weight (Fig. 1). A total of 2411 (39%) patients lost weight, and 3735 (61%) patients gained weight (Table 1). We observed that 87 (1%) of patients were underweight (BMI < 18.5), 2058 (33%) were normal weight (18.5 ≤ BMI < 25), 1376 (22%) were overweight (25 ≤ BMI < 30) and 2625 (43%) were obese (BMI > 30). From analysis of the transitions between normal/underweight, overweight, and obese, we observed that after 10 years, of the patients who were underweight, 65% stayed underweight, 32% became normal weight, 2% became overweight, and 2% became obese. After 10 years, of the patients who were normal weight, 3% became underweight, 78% stayed normal weight, 17% became overweight, and 2% became obese. Of the patients who were overweight, 71% stayed overweight, 0% became underweight, 14% became normal weight, and 15% became obese. Of the patients who were obese, 84% stayed obese, 0% became underweight, 1% became normal weight, and 14% became overweight.

CONCLUSIONS

United States adults are at risk of transitioning from normal weight to becoming overweight or obese. Covariate dependent Markov chains constructed with gradient boost modeling can effectively generate long-term predictions.

"I Often Feel Conflicted in Denying Surgery": Perspectives of Orthopaedic Surgeons on Body Mass Index Thresholds for Total Joint Arthroplasty: A Qualitative Study

BACKGROUND

Use of a patient body mass index (BMI) eligibility threshold for total joint arthroplasty (TJA) is controversial. A strict BMI criterion may reduce surgical complication rates, but over-restrict access to effective osteoarthritis (OA) treatment. Factors that influence orthopaedic surgeons' use of BMI thresholds are unknown. We aimed to identify and explore orthopaedic surgeons' perspectives regarding patient BMI eligibility thresholds for TJA.

METHODS

A cross-sectional, online qualitative survey was distributed to orthopaedic surgeons who conduct hip and/or knee TJA in the United States. Survey questions were open-ended, and responses were collected anonymously. Survey data were coded and analyzed in an iterative, systematic process to identify predominant themes.

RESULTS

Forty-five surveys were completed. Respondents were 54.3 ± 12.4 years old (range, 34 to 75 years), practiced in 22 states, and had 21.2 ± 13.3 years (range, 2 to 44 years) of surgical experience. Twelve factors influencing BMI threshold use by orthopaedic surgeons were identified: (1) evidence interpretation, (2) personal experiences, (3) difficulty of surgery, (4) professional ramifications, (5) ethics and biases, (6) health-system policies and performance metrics, (7) surgical capacity and resources, (8) patient body fat distribution, (9) patient self-advocacy, (10) control of decision-making in the clinical encounter, (11) expectations for demonstrated weight loss, and (12) research and innovation gaps.

CONCLUSIONS

Multilevel, complex factors underlie BMI threshold use for TJA eligibility. Addressing identified factors at the patient, surgeon, and health-system levels should be considered to optimally balance complication avoidance with improving access to life-enhancing surgery.

CLINICAL RELEVANCE

This study may influence how orthopaedic surgeons think about their own practices and how they approach patients and consider surgical eligibility.