Abstract
Background
The causes of obesity are multifactorial, with genetic, environmental, behavioural and societal contributions. These factors also affect adherence to diet and exercise after bariatric surgery. The objective of this study was to evaluate changes in perceived obesity-related stigma, exercise and dietary adherence perioperatively as well as what demographic factors most influence the magnitude of these changes.
Methods
Validated questionnaires regarding perception of stigma and adherence to diet and exercise regimens were administered to 104 bariatric surgery patients preoperatively and postoperatively at three, six and 12 months. Scoring was compared for improvement, and concomitant factors were analysed for effect on magnitude of improvement.
Results
Our study found overall improvement in perception of stigma as well as adherence to diet and exercise regimens. Those with a family history of obesity had less robust improvement compared to those without a family history of obesity. Those who were Caucasian also did not have as robust of an improvement in their scores.
Conclusions
Patient perception of obesity-related stigma and adherence to diet and exercise regimens improve after bariatric surgery. However, a patient with a family history of obesity and/or a Caucasian ethnicity may have a less robust improvement in these facets.
Introduction
The cause of obesity is multifaceted and is a complex health issue to address. Obesity is defined as having a body mass index (BMI) of 30 or greater (National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) 2018), and results from an amalgamation of causes and other contributing factors. Individual factors include behavioural characteristics (Pengpid & Peltzer 2017), dietary modifications, environmental factors and genetic contributions (Rask-Andersen et al 2017, Visscher et al 2012, Zaitlen et al 2013). It has been argued that about 40–70% of inter-individual variability in BMI, which is frequently used to assess obesity, has been attributed to genetic factors (Rask-Andersen et al 2017, Visscher et al 2012, Zaitlen et al 2013). Additionally, an individual’s response to environmental stimuli differs depending on the expressed genotype, or from epigenetic effects that vary between groups of individuals depending on their lifestyles and environment (Rask-Andersen et al 2017).
While there is increasing evidence for the importance of genetics in predisposing individuals to obesity (Rask-Andersen et al 2017, Visscher et al 2012, Zaitlen et al 2013), studies have also found significant familial influences related to one’s predisposition to obesity (Horwitz & Neiderhiser 2011, Serra-Majem & Bautista-Castaño 2013). Families share models for dietary-relevant behaviour, such as poor eating habits (Sedibe et al 2018, Serra-Majem & Bautista-Castaño 2013) and physical activity patterns that can also significantly contribute to obesity (Sedibe et al 2018, Strasser 2013). Family behavioural patterns can be influenced by other exposures such as education and development of life skills (Puhl & Heuer 2010).
This study employed a quantitative approach to evaluate changes in exercise and dietary adherence perioperatively. Furthermore, we examined what demographic factors influence the magnitude of these aforementioned changes.
Methods
A quantitative methodological approach was used to assess adherence to diet and exercise (DaE) pre and postbariatric surgery. Patients approved for bariatric surgery via our academic tertiary care centre Bariatric Surgery protocol, were informed of the study, procedures, potential risks and benefits. Those agreeable for study participation completed validated self-administered questionnaires regarding DaE metrics. Patients completed questionnaires approximately one month prior to surgery and then again postoperatively at three, six and 12-month follow-ups. The study was approved by the hospital Institutional Review Board. Questionnaire scoring was compared for improvement, and demographic factors were analysed to determine their influence on the magnitude of the changes seen in the final scoring reports.
Scale validity
Daily physical activity and eating behaviours were assessed using the SRAEB – a descriptive survey developed for the purposes of this study. Items were compiled based on recommended levels of physical activity and healthful eating patterns by the US Department of Health and Human Services (2018) and research investigating predictive patterns of eating on health (Herazo-Beltrán et al 2017, Pengpid & Peltzer 2017). Items were designed to yield descriptive information on frequency of participation in physical activity, use of activity for transportation (walking, biking), daily eating patterns including breakfast, snacking and eating frozen or processed meals vs home-cooked foods. Participants reported the frequency of behaviours ranging from never (1) to seven days a week (5). A confirmatory factor analysis yielded four different factors with satisfactory internal consistencies: cooking at home (α =.80), eating prepared or frozen meals (α =.81), participation in physical activity (α =.70) and snacking behaviour (α =.83). Five items measuring exercise (ie: walking or bicycling) as transportation and frequency of eating out did not load onto any factors and were therefore eliminated from the analysis.
Patient sample
Our study sample included 104 participants, of whom over half (n = 57) were men. Ages ranged from 22 to 72 years of age with a mean age of 44.28 years. The age group distribution included: 20–29 (12.7%), 30–39 (22.22%), 40–49 (30.16%), 50–59 (20.63%), 60–69 (12.70%), ≥70 (1.59%). More than 50 per cent (50.96%) of the patients were Caucasian, (12.5%) were African American and the remainder (36.99%) included: Asian, Hispanic and non-responders. Inclusion criteria were that participants must be ≥18 years of age with a BMI ≥ 35 and consenting to undergo any type of bariatric surgery. There were no unique factors for exclusion that were not identified by the aforementioned inclusion criteria. Preoperative BMI ranged from 35.87 to 75.66. Range: BMI 35–39.99 (9.09%), 40–49.99 (53.25%), 50–59.99 (25.97%), 60–69.99 (7.79%), ≥70 (3.90%). Over two-thirds (77%) of our population had a family history of obesity. A quarter (25%) admitted to a smoking history and one third (34%) had a history of hypertension. Less than a quarter (17%) had a history of diabetes mellitus and 5% had hypothyroidism. Medical diagnostic history included both a subjective listing of diagnoses as well as a confirmatory analysis of the patients’ medication regimen to include treatment that correlated with the documented diagnosis. Nearly half (48%) of our sample were married. Over half (53.65%) underwent Roux-en-Y Gastric Bypass and the others (46.35%) underwent vertical sleeve gastrectomy. The postoperative improvement in BMI ranged from 1.44 points to 30.77 points. BMI improvement range: Improved <10 (16.88%), 10–19.99 (66.23%), 20–29.99 (15.58%) and ≥30 (1.29%).
Statistical analysis
Summary and descriptive statistics were generated for all patients regarding their surgical and sociodemographic characteristics. The SRAEB scales were characterised and sorted into differentiation of improvement versus no improvement. Outcomes variables included: pre and postsurgery SRAEB scores. Explanatory variables included: age, gender, race, marital status, family history of obesity, pre versus postoperative BMI, type of surgery and features of their medical history such as smoking, hypertension, diabetes mellitus and/or hypothyroidism. Multivariate linear regression models were employed to assess the relationships between improvement in the outcome variables and the explanatory variables. Due to the lack of patient response on the demographic surveys, education and employment status were not included in the final linear regression. Levels of significance were assessed using t-test regression coefficients. P-values less than 0.05 were considered statistically significant. Data were analysed using R statistical software via the R Foundation for Statistical Computing 2017 (version 3.43, Vienna, Austria).
Results
The 104 participants in the study were asked to provide presurgical historical/demographic information. In regards to SCQ and SRAEB comparative data, 72.63% provided comparison data for three months, 75.78% provided data at six months and 63.15% provided data at 12 months. Nearly two-thirds (65%) showed an improvement on the SRAEB scores. When considering factors that had a statistically significant effect on influencing the score comparisons, two factors demonstrated influence in the SRAEB scores: family history of obesity and ethnicity (see Table 1).
Participation in physical activity and nutrition-magnitude of improvement.
Hx: history; BMI: body mass index.
aReference groups.
bStatistically significant level: p < 0.05.
Our results showed that participants who identified as Caucasian still showed a global improvement in their questionnaire scoring; however, on average, their scores were less prominently improved in comparison to the other races/ethnicities represented in our sample, with a negative coefficient of 5.552 (P = 0.010). Those with a family history of obesity similarly showed improvement in their scores on a global basis, but they too demonstrated a lower magnitude of improvement in comparison to those who did not have a family history of obesity. Having this family history demonstrated a negative coefficient of 6.427 (P = 0.004). Our data did not demonstrate statistically significant differences of the magnitude of change in the SCQ or SRAEB scoring among socio-demographic factors such as age, gender, type of surgery, improvement in BMI, marital status, smoking history, history of diabetes or hypothyroidism.
Discussion
In this study, we examined the changes seen in dietary adherence perioperatively. We also explored demographic factors that influence the magnitude of these changes. Our study found that the majority of patients who underwent bariatric surgery felt that they were more likely to be involved in more positive dietary habits and more frequent physical activity. These findings are congruent with the current literature (Angrisani et al 2015, Herazo-Beltrán et al 2017). In regards to factors that affected the magnitude of change in dietary habits and physical activity, two factors demonstrated statistical significance: a family history of obesity and ethnicity. To elaborate, these two factors held a negative coefficient of effect; in other words, those with a family history of obesity and those under the Caucasian classification still demonstrated an improvement in their evaluation scoring; however, the magnitude was not as robust as those who did not hold this history. Our results indicate that those with either of these two historical descriptions scored an average of >5 points less than those without these demographic characteristics. Specifically having a family history of obesity held a negative coefficient of 6.427 (P = 0.004) and a Caucasian ethnicity held a negative coefficient of 5.552 (P = 0.010).
These findings reinforce the importance of family dynamic, environmental factors that influence eating and exercise behaviours and the genetic correlations that influence obesity (Horwitz & Neiderhiser 2011, Rask-Andersen et al 2017, Sedibe et al 2018, Visscher et al 2012, Zaitlen et al 2013). For example, evidence has shown that for children ≤5 years of age, the BMI of their parents is more predictive of developing obesity in the future than the child’s actual weight (Horwitz & Neiderhiser 2011). This also alludes to the difficulty of teaching and demonstrating proper dietary and exercise behaviours if one does not know the factual and nutritional information and/or if one does not maintain these habits on a regular basis. The evidence for genetic influence on anthropometry has been estimated to be 60–70% based on twin studies (Hasselbalch 2010). Therefore, it is understandable that family history confers a predisposition; however, this also allows 30–40% to be based on environmental factors. It should be kept in mind that a strong interaction exists between genetics and the environment, to the extent that one’s environment can influence the expression of certain genes (Horwitz & Neiderhiser 2011). For instance, one study showed that the effect of the genetic score for BMI was 2.5 times higher in participants who reported having a slow walking pace compared to those who had a brisk walking pace (Zaitlen et al 2013). To be clear, having a family history does not preclude one from having success in their diet and exercise regimen, rather it is an important influence to be aware of when considering the effort necessary to maintain a healthy lifestyle.
Although our study elucidates the influence of familial history on likelihood to maintain healthy diet and exercise regimens post bariatric surgery, we must recognise a number of important limitations. First, we explored a relatively large number of independent variables with a sample of modest size; therefore, we may not have had sufficient power to detect associations between some sociodemographic factors such as level of education and employment status. Also, a self-report method of evaluation may be more likely to impose a response bias when discussing exercise and dietary adherence. The limitations underscored in this study, however, provide important areas to prioritise in further studies on factors that influence postoperative adherence to diet and exercise recommendations.
Conclusion
This study presents evidence to support that the majority of patients who undergo bariatric surgery will show an improvement in their dietary and exercise adherence; however, those with a family history of obesity may encounter more barriers to maintaining a healthy diet and exercise regimen postbariatric surgery. Potential focuses for future research would include long-term outcome data analysis evaluating the influence of a family history of obesity on weight regain years after bariatric surgery.
No competing interests declared
