Unhealthy diet pattern mediates the disproportionate prevalence of obesity among adults with socio-economic disadvantage : an Australian representative cross-sectional study

The role of unhealthy dietary pattern in the association between socio-economic factors and obesity is unclear. The aim was to examine the association between socio-economic disadvantage and obesity and to assess mediation effect of unhealthy dietary pattern defined using the Mediterranean diet criteria. The data source was the Australian National Nutrition and Physical Activity Survey. The study sample included 7744 participants aged 18 years and over, 28% of whom had obesity. We used the Australian Socio-Economic Indexes for Areas (SEIFA) classification system for categorizing socio-economic disadvantage; calculated the Mediterranean Diet Score (MDS) using standard criteria; and used measured body mass index to define obesity. We conducted a mediation analysis using log–binomial models to generate the prevalence ratio for obesity and the proportion mediated by the MDS. The most disadvantaged group was associated with higher level of obesity after controlling for covariates (1.40, 95% CI 1.25, 1.56) compared to the least disadvantaged group, and in a dose–response way for each decreasing SEIFA quintile. The relationship between socio-economic disadvantage and obesity was mediated by the MDS (4.0%, 95% CI 1.9, 8.0). Public health interventions should promote healthy dietary patterns, such as the Mediterranean diet, to reduce obesity, especially in communities with high socio-economic disadvantage

Micronutrient deficiencies and anaemia associated with body mass index in Australian adults : a cross-sectional study

Aim To estimate the prevalence of micronutrient deficiencies and anaemia, and their association with body mass index (BMI) categories among Australian adults. Method We analysed data from the 2011–2013 Australian Health Survey from 3539 participants aged 18 years and over (without known pregnancy) with measured weight and height, and nutrient biomarkers. To address complex sampling, survey weights were used when estimating the prevalence of micronutrient deficiencies (vitamin B12 deficiency; serum vitamin B12<145 pmol/L; iron deficiency; ferritin<30 µg/L and vitamin D deficiency; 25-hydroxyvitamin D<50 nmol/L) and anaemia (haemoglobin <120 g/L for females and <130 g/L for males) and when assessing associations with logistic regression models with adjusted ORs (AORs) for BMI categories: healthy weight (BMI 18.5 to <25.0 kg/m2 ), reference; overweight (BMI 25.0 to <30.0 kg/m2 ), obesity class I (BMI 30.0 to <35.0 kg/m2 ), obesity class II/III (BMI 35.0 kg/m2 or more). Result The prevalence of vitamin B12 deficiency (range 0.9%─2.8%) and anaemia (range 3.9%─6.7%) were variable across BMI groups. The prevalence of iron deficiency in the obesity class I group was 12.0 percentage points lower than healthy weight group with an AOR of 0.50 (95% CI 0.30 to 0.83). The prevalence of vitamin D deficiency in the obesity class II/III group was 7.9 percentage points higher than the healthy weight group with an AOR of 1.62 (95% CI 1.01 to 2.60). Vitamin B12 deficiency and anaemia were not consistently associated with BMI groups. Conclusion We found a consistent association between severe obesity and vitamin D deficiency in Australian adults. We also found obesity class I was negatively associated with iron deficiency, whereas there was no consistent association between BMI groups and vitamin B12 deficiency and anaemia. Public health strategies are needed to prevent vitamin D deficiency in this high-risk population

A predictive model for non-completion of an intensive specialist obesity service in a public hospital : a case-control study

Background: Despite the growing evidence base supporting intensive lifestyle and medical treatments for severe obesity, patient engagement in specialist obesity services is difficult to achieve and poorly understood. To address this knowledge gap, we aimed to develop a model for predicting non-completion of a specialist multidisciplinary service for clinically severe obesity, termed the Metabolic Rehabilitation Programme (MRP). Method: Using a case-control study design in a public hospital setting, we extracted data from medical records for all eligible patients with a body mass index (BMI) of ≥35 kg/m2 with either type 2 diabetes or fatty liver disease referred to the MRP from 2010 through 2015. Non-completion status (case definition) was coded for patients whom started but dropped-out of the MRP within 12 months. Using multivariable logistic regression, we tested the following baseline predictors hypothesised in previous research: age, gender, BMI, waist circumference, residential distance from the clinic, blood pressure, obstructive sleep apnoea (OSA), current continuous positive airway pressure (CPAP) therapy, current depression/anxiety, diabetes status, and medications. We used receiver operating characteristics and area under the curve to test the performance of models. Results: Out of the 219 eligible patient records, 78 (35.6%) non-completion cases were identified. Significant differences between non-completers versus completers were: age (47.1 versus 54.5 years, p &lt; 0.001); residential distance from the clinic (21.8 versus 17.1 km, p = 0.018); obstructive sleep apnoea (OSA) (42.9% versus 56.7%, p = 0.050) and CPAP therapy (11.7% versus 28.4%, p = 0.005). The probability of non-completion could be independently associated with age, residential distance, and either OSA or CPAP. There was no statistically significant difference in performance between the alternate models (69.5% versus 66.4%, p = 0.57). Conclusions: Non-completion of intensive specialist obesity management services is most common among younger patients, with fewer complex care needs, and those living further away from the clinic. Clinicians should be aware of these potential risk factors for dropping out early when managing outpatients with severe obesity, whereas policy makers might consider strategies for increasing access to specialist obesity management services

Association of husbands' education status with unintended pregnancy in their wives in southern Ethiopia : a cross-sectional study

Background: Unintended pregnancy rates are substantially higher in developing regions, have significant health consequences, and disproportionately affect subgroups with socio-economic disadvantage. We aimed to examine whether there is an association between husbands’ education status and their wives unintended pregnancy in southern Ethiopia. Methods: The data source for this study was from a cross-sectional study on iron-folate supplementation and compliance in Wolaita, South Ethiopia. Data were collected from October to November 2015 in 627 married pregnant women regarding their husbands’ education status, socio-demographic characteristics, and if they wanted to become pregnant at the time of survey using an interviewer administered questionnaire. Logistic regression was used to estimate Odds Ratios (ORs) with associated z-tests and 95% Confidence Intervals (95% CI) for variables associated with unintended pregnancy. Results: The proportion of unintended pregnancy in this sample was 20.6%. Husbands’ education status, age, residence, and using family planning methods were associated with unintended pregnancy (all P-values < 0.05). Multivariable models consistently showed that being married to a husband with at least some college or university education was associated with a decreased OR for unintended pregnancy after controlling for age and use of family planning at conception period (OR 0.36 [95%CI: 0.17, 0.82]) and age and rural residence (OR 0.40 [95%CI: 0.18, 0.90]). Conclusion: Unintended pregnancy among Ethiopian woman was consistently associated with being married to least educated husbands in southern Ethiopia. Increasing age and living in a rural vs urban area were also independently associated with unintended pregnancy. Strategies for addressing family planning needs of women with poorly educated husbands should be the subject of future research

The performance of mid-upper arm circumference for identifying children and adolescents with overweight and obesity : a systematic review and meta-analysis

Objective: This study aimed to synthesise the existing evidence on the performance of mid-upper arm circumference (MUAC) to identify children and adolescents with overweight and obesity. Design: Systematic review and meta-analysis. Setting: We searched PubMed, EMBASE, SCOPUS, Cochrane Library, Web of Science, CINAHL and Google scholar databases from their inception to December 10, 2021, for relevant studies. There were no restrictions regarding the language of publication. Studies reporting measures for the diagnostic performance of MUAC compared with a reference standard for diagnosing overweight and obesity in children and adolescents aged 2–19 years were included. Participants: A total of 54 381 children and adolescents from twenty-one studies were reviewed; ten studies contributed to meta-analyses. Results: In boys, MUAC showed a pooled AUC of 0·92 (95 % CI 0·89, 0·94), sensitivity of 84·4 (95 % CI 84·6, 90·8) and a specificity of 86·0 (95 % CI 79·2, 90·8), when compared against BMI z-score, defined overweight and obesity. As for girls, MUAC showed a pooled AUC of 0·93 (95 % CI 0·90, 0·95), sensitivity of 86·4 (95 % CI 79·8, 91·0), specificity of 86·6 (95 % CI 82·2, 90·1) when compared against overweight and obesity defined using BMI z-scores. Conclusion: In comparison with BMI, MUAC has an excellent performance to identify overweight and obesity in children and adolescents. However, no sufficient evidence on the performance of MUAC compared with gold standard measures of adiposity. Future research should compare performance of MUAC to the ‘golden standard’ measure of excess adiposity

Clinical usefulness of brief screening tool for activating weight management discussions in primary cARE (AWARE) : a nationwide mixed methods pilot study

Objective The Edmonton Obesity Staging System (EOSS) is based on weight related health complications among individuals with overweight and obesity requiring clinical intervention. We aimed to assess the clinical usefulness of a new screening tool based on the EOSS for activating weight management discussions in general practice. Methods We enrolled five General Practitioners (GPs) and 25 of their patients located nationwide in metropolitan areas of Australia to test the feasibility, acceptability, and accuracy of the new ‘EOSS-2 Risk Tool’, using cross-sectional and qualitative study designs. Diagnostic accuracy of the tool for the presence of EOSS ≥2 criteria was based on clinical information collected prospectively. To assess feasibility and applicability, we explored the views of GP and patient participants by thematic analysis of transcribed verbatim and de-identified data collected by semi-structured telephone interviews. Results Nineteen (76%) patients were aged ≥45 years, five (20%) were male, and 20 (80%) were classified with obesity. All 25 patients screened positive for EOSS ≥2 criteria by the tool. Interviews with patients continued until data saturation was reached resulting in a total of 23 interviews. Our thematic analysis revealed five themes: GP recognition of obesity as a health priority (GPs expressed strong interest in and understanding of its importance as a health priority); obesity stigma (GPs reported the tool helped them initiate health based and non-judgmental conversations with their patients); patient health literacy (GPs and patients reported increased awareness and understanding of weight related health risks), patient motivation for self-management (GPs and patients reported the tool helped focus on self-management of weight related complications), and applicability and scalability (GPs stated it was easy to use, relevant to a range of their patient groups, and scalable if integrated into existing patient management systems). Conclusion The EOSS-2 Risk Tool is potentially clinically useful for activating weight management discussions in general practice. Further research is required to assess feasibility and applicability

Development and internal validation of the Edmonton Obesity Staging System-2 Risk screening Tool (EOSS-2 Risk Tool) for weight-related health complications : a case-control study in a representative sample of Australian adults with overweight and obesity

Objective Excess weight and related health complications remain under diagnosed and poorly treated in general practice. We aimed to develop and validate a brief screening tool for determining the presence of unknown clinically significant weight-related health complications for potential application in general practice. Design We considered 14 self-reported candidate predictors of clinically significant weight-related health complications according to the Edmonton Obesity Staging System (EOSS score of ≥2) and developed models using multivariate logistic regression across training and test data sets. The final model was chosen based on the area under the receiver operating characteristic curve and the Hosmer-Lemeshow statistic; and validated using sensitivity, specificity and positive predictive value. Setting and participants We analysed cross-sectional data from the Australian Health Survey 2011–2013 sample aged between 18 and 65 years (n=7518) with at least overweight and obesity. Results An EOSS≥2 classification was present in 78% of the sample. Of 14 candidate risk factors, 6 (family history of diabetes, hypertension, high sugar in blood/urine, high cholesterol and self-reported bodily pain and disability) were automatically included based on definitional or obvious correlational criteria. Three variables were retained in the final multivariate model (age, self-assessed health and history of depression/anxiety). The EOSS-2 Risk Tool (index test) classified 89% of those at ‘extremely high risk’ (≥25 points), 67% of those at ‘very high risk’ (7–24 points) and 42% of those at ‘high risk’ (<7 points) of meeting diagnostic criteria for EOSS≥2 (reference). Conclusion The EOSS-2 Risk Tool is a simple, safe and accurate screening tool for diagnostic criteria for clinically significant weight-related complications for potential application in general practice. Research to determine the feasibility and applicability of the EOSS-2 Risk Tool for improving weight management approaches in general practice is warranted

Enablers and barriers to implementing obesity assessments in clinical practice : a rapid mixed-methods systematic review

Objectives This systematic review aims to improve our knowledge of enablers and barriers to implementing obesity-related anthropometric assessments in clinical practice. Design A mixed-methods systematic review. Data sources Medline, Embase and CINAHL to November 2021. Eligibility criteria Quantitative studies that reported patient factors associated with obesity assessments in clinical practice (general practice or primary care); and qualitative studies that reported views of healthcare professionals about enablers and barriers to their implementation. Data extraction and synthesis We used randomeffects meta-analysis to pool ratios for categorical predictors reported in ≥3 studies expressed as pooled risk ratio (RR) with 95% CI, applied inverse variance weights, and investigated statistical heterogeneity (I2 ), publication bias (Egger’s test), and sensitivity analyses. We used reflexive thematic analysis for qualitative data and applied a convergent integrated approach to synthesis. Results We reviewed 22 quantitative (observational) and 3 qualitative studies published between 2004 and 2020. All had ≥50% of the quality items for risk of bias assessments. Obesity assessment in clinical practice was positively associated with patient factors: female sex (RR 1.28, 95% CI 1.10 to 1.50, I2 99.8%, mostly UK/USA), socioeconomic deprivation (RR 1.21, 95% CI 1.18 to 1.24, I2 73.9%, UK studies), non-white race/ ethnicity (RR 1.27, 95% CI 1.03 to 1.57, I2 99.6%) and comorbidities (RR 2.11, 95% CI 1.60 to 2.79, I2 99.6%, consistent across most countries). Obesity assessment was also most common in the heaviest body mass index group (RR 1.55, 95% CI 0.99 to 2.45, I2 99.6%). Views of healthcare professionals were positive about obesity assessments when linked to patient health (convergent with meta-analysis for comorbidities) and if part of routine practice, but negative about their role, training, time, resources and incentives in the healthcare system. Conclusions Our evidence synthesis revealed several important enablers and barriers to obesity assessments that should inform healthcare professionals and relevant stakeholders to encourage adherence to clinical practice guideline recommendations

W05-01 - Lifestyle programs integrated within collaborative for the management of co-morbid diabetes and depression

The prevalence of both type 1 and type 2 diabetes mellitus (diabetes) is disproportionately high in people with clinically significant depression. Lifestyle programs are recommended for the management of diabetes, but are difficult to implement in practice, particularly for depressed people who are least likely to adhere to healthy lifestyle recommendations. In addition, interventions recommended for the management of depression have limited impact on diabetes outcomes and do not take into account lifestyle risk factors. The aim of this presentation is to inform policy and decision-making on the organization and delivery of effective multidisciplinary care for the management of co-morbid diabetes and depression

Obesity and increased risk of type 2 diabetes mellitus : the aetiological role of depression

Obesity, defined using body mass index (BMI) values ≥30 kg/m2 (calculated as weight in kilograms divided by height in meters squared), is a serious medical condition almost entirely due to excess dietary intake. It is estimated that 205 million men and 297 million women older than 20 years worldwide were obese in 2008 [1]. The age-standardised prevalence of obesity was approximately 10% in men and 14% in women — nearly double the 1980 prevalence estimates. One of the most important consequences of high and rising trends in global obesity prevalence has been the increasing number of people developing type 2 diabetes mellitus (T2DM) [2]. Indeed, the International Diabetes Federation (IDF) reports that some 366 million people worldwide, or 8% of adults, are now estimated to have diabetes, and that lifestyle therapy should be used to achieve a healthy BMI in the prevention and management of T2DM [3]. The rising health and economic burden of T2DM disproportionately affect older, obese, and physical inactive people [4], as well as those with depression [5]. Reliable information about the aetiological role of depression in obesity and consequential T2DM could lead to more effective management and prevention planning, resulting in significant health and economic benefits