Associations of BMI, waist circumference, body fat, and skeletal muscle with type 2 diabetes in adults.

AIMS: Type 2 diabetes (T2D) is known to be associated with high BMI and waist circumference (WC). These measures do not discriminate well between skeletal muscle (SM) and body fat (BF), which may have opposite influences. METHODS: We conducted a secondary analysis of population-based data from 58,128 aged 18-85 yrs from Scottish Health Surveys (2003, 2008-2011) and Health Surveys for England (2003-2006, 2008-2013), excluding pregnant women and insulin-treated diabetes. Logistic regression was used to assess associations of known T2D, and of screened HbA1c > 48 mmol/mol (> 6.5%), with sex-specific quintiles of BMI, WC, and BF% and SM% estimated by validated anthropometric equations, adjusted for age, sex, smoking, ethnicity, country, and survey year. RESULTS: As expected, ORs for having known T2D rose with quintiles of BMI (1, 1.5, 2.3, 3.1, and 6.5) and WC (1, 1.8, 2.5, 3.5, and 8.7). Compared to the lowest BF% quintile, OR for having T2D in highest BF% quintile was 11.1 (95% CI = 8.4-14.6). Compared to the highest SM% quintile, OR for having T2D in lowest SM% quintile was 2.0 (1.7-2.4). Of 72 adults with T2D/HbA1c > 6.5% in the lowest quintile of BF%, 27 (37.5%) were in quintile 1 of SM%. Similar patterns of OR were observed for having HbA1c > 6.5% in those without known T2D. CONCLUSIONS: Estimated BF% associates strongly with T2D. Low SM% also has a significant association, suggesting a neglected aspect of aetiology within T2D. These two simple measures with biological relevance, available from data collected in most health surveys, may be more useful than the purely statistical terms BMI.

Filling the intervention gap: service evaluation of an intensive nonsurgical weight management programme for severe and complex obesity.

BACKGROUND: Weight management including formula total diet replacement (TDR) is emerging as an effective intervention for severe and complex obesity, particularly with respect to type 2 diabetes (T2DM). However, no prospective audit and service evaluation of such programmes have been reported. METHODS: Following initial feasibility piloting, the Counterweight-Plus programme was commissioned across a variety of healthcare providers. The programme includes: Screening, TDR (formula low energy diet), food reintroduction and weight loss maintenance, all delivered by staff with 8 h of training, in-service mentoring, ongoing specialist support and access to medical consultant expertise. Anonymised data are returned centrally for clinical evaluation. RESULTS: Up to December 2016, 288 patients commenced the programme. Mean (SD) baseline characteristics were: age 47.5 (12.7) years, weight 128.0 (32.0) kg, body mass index 45.7 (10.1) kg m-2 , n = 76 (26.5%) were male and n = 99 (34.5%) had T2DM. On an intention-to-treat (ITT) basis, a loss of ≥15 kg at 12 months was achieved by 48 patients, representing 22.1% of all who started and 40% of those who maintained engagement. For complete cases, mean (95% confidence interval) weight loss was 13.3 (12.1-14.4) kg at 3 months, 16.0 (14.4-17.6) kg at 6 months and 14.2 (12.1-16.3) kg at 12 months (all P < 0.001), with losses to follow-up of 10.8%, 29.3% and 44.2%, respectively. Mean loss at 12 months by ITT analyses was: single imputation -10.5 (9.5) kg, last observation carried forward -10.9 (11.6) kg and baseline observation carried forward -7.9 (11.1) kg. The presence of diabetes had no significant impact on weight change outcomes. CONCLUSIONS: This nonsurgical approach is effective for many individuals with severe and complex obesity, representing an option before considering surgery. The results are equally effective in terms of weight loss for people with T2DM.

Different associations between body composition and alcohol when assessed by exposure frequency or by quantitative estimates of consumption.

BACKGROUND: Alcohol intake is widely assumed to contribute to excess body fatness, especially among young men; however, the evidence is inconsistent. We have addressed this research question by investigating associations between reported alcohol consumption and body composition from large representative national surveys in a high alcohol-consuming country with a high obesity prevalence. METHODS: The present study comprised a secondary analysis of combined cross-sectional nationally representative Scottish Health Surveys (1995-2010). Reported alcohol-drinking frequency was divided into five groups: from 'nonfrequent drinking' (reference) to daily/'almost every day' among 35 837 representative adults [mean (SD) age: 42.7 (12.7) years (range 18-64 years)]. Quantitative alcohol consumption was categorised into seven groups: from '1-7 to ≥50 10 g units per week'. Regression models against measured body mass index (BMI) and waist circumference (WC) were adjusted for age, physical activity, income, smoking, deprivation category and economic status. RESULTS: Among alcohol-consuming men, heavier drinking (21-28 units per week) was associated with a higher BMI by +1.4 kg m-2 [95% confidence interval (CI) = 1.38-1.43] and higher WC by +3.4 cm (95% CI = 3.2-3.6) than drinking 1-7 units per week. However, those who reported daily drinking frequency were associated with a lower BMI by -2.45 kg m-2 (95% CI = -2.4 to -2.5) and lower WC by -3.7 cm (95% CI = -3.3 to -4.0) than those who reported less-frequent drinking. Similar associations were found for women. Most of these associations were restricted to subjects aged >30 years. Unexplained variances in BMI and WC are large. CONCLUSIONS: Quantitative alcohol consumption and frequency of consumption were positively and inversely associated, respectively, with both BMI and WC among alcohol-consuming adults. Surveys are needed that evaluate both the quantity and frequency of consumption. The lowest BMI and WC were associated with a 'Mediterranean' drinking style (i.e. relatively little, but more frequently).

Ethnicity and risk of cardiovascular disease (CVD): 4.8 year follow-up of patients with type 2 diabetes living in Scotland.

AIMS/HYPOTHESIS: Potential differences in cardiovascular risk by ethnicity remain uncertain. We evaluated the association of ethnicity with cardiovascular disease (CVD) incidence in a large cohort of people with type 2 diabetes living in Scotland. METHODS: Data from Scottish Care Information-Diabetes (SCI-Diabetes) were linked to Scottish Morbidity Records (SMR01) and National Records of Scotland data for mortality for dates between 2005 and 2011. Of 156,991 people with type 2 diabetes with coded ethnicity, 121,535 (77.4%) had no CVD at baseline (White: 114,461; Multiple Ethnic: 2,554; Indian: 797; Other Asian: 319; Pakistani: 2,250; Chinese: 387; African-Caribbean: 301 and Other: 466) and were followed up (mean ± SD: 4.8 ± 2.3 years) for the development of fatal and non-fatal CVD. RESULTS: During follow-up, 16,265 (13.4%) patients developed CVD (ischaemic heart or cerebrovascular diseases). At baseline, Pakistanis were younger and had developed diabetes earlier, had higher HbA1c and longer duration of diabetes, but had lower BP, BMI, creatinine, proportion of smokers and proportion on antihypertensive therapy than whites. The age and sex adjusted HRs for CVD were HR 1.31 (CI 1.17, 1.47), p < 0.001 in Pakistanis and HR 0.66 (CI 0.47, 0.92), p = 0.014 in Chinese compared with whites. Adjusting additionally for an area measure of deprivation, duration of diabetes, conventional CVD and other risk factors, the HR for Pakistanis (HR 1.45 [CI 1.14, 1.85], p = 0.002) was significantly higher, and that for Chinese (HR = 0.58 [CI 0.24, 1.40], p = 0.228) lower, compared with whites. CONCLUSIONS/INTERPRETATION: Compared with whites with type 2 diabetes, those of Pakistani ethnicity in Scotland were at increased risk of CVD, whereas Chinese were at lower risk, with these differences unexplained by known risk factors.

The effect of deprivation and HbA1c on admission to hospital for diabetic ketoacidosis in type 1 diabetes.

AIMS/HYPOTHESIS: Diabetic ketoacidosis is a potentially life-threatening complication of diabetes and has a strong relationship with HbA(1c). We examined how socioeconomic group affects the likelihood of admission to hospital for diabetic ketoacidosis. METHODS: The Scottish Care Information - Diabetes Collaboration (SCI-DC), a dynamic national register of all cases of diagnosed diabetes in Scotland, was linked to national data on hospital admissions. We identified 24,750 people with type 1 diabetes between January 2005 and December 2007. We assessed the relationship between HbA(1c) and quintiles of deprivation with hospital admissions for diabetic ketoacidosis in people with type 1 diabetes adjusting for patient characteristics. RESULTS: We identified 23,479 people with type 1 diabetes who had complete recording of covariates. Deprivation had a substantial effect on odds of admission to hospital for diabetic ketoacidosis (OR 4.51, 95% CI 3.73, 5.46 in the most deprived quintile compared with the least deprived). This effect persisted after the inclusion of HbA(1c) and other risk factors (OR 2.81, 95% CI 2.32, 3.39). Men had a reduced risk of admission to hospital for diabetic ketoacidosis (OR 0.71, 95% CI 0.63, 0.79) and those with a history of smoking had increased odds of admission to hospital for diabetic ketoacidosis by a factor of 1.55 (95% CI 1.36, 1.78). CONCLUSIONS/INTERPRETATION: Women, smokers, those with high HbA(1c) and those living in more deprived areas have an increased risk of admission to hospital for diabetic ketoacidosis. The effect of deprivation was present even after inclusion of other risk factors. This work highlights that those in poorer areas of the community with high HbA(1c) represent a group who might be usefully supported to try to reduce hospital admissions.

Inpatient costs for people with type 1 and type 2 diabetes in Scotland: a study from the Scottish Diabetes Research Network Epidemiology Group.

AIMS/HYPOTHESIS: The rising prevalence of diabetes worldwide has increased interest in the cost of diabetes. Inpatient costs for all people with diabetes in Scotland were investigated. METHODS: The Scottish Care Information-Diabetes Collaboration (SCI-DC), a real-time clinical information system of almost all diagnosed cases of diabetes in Scotland, UK, was linked to data on all hospital admissions for people with diabetes. Inpatient stay costs were estimated using the 2007-2008 Scottish National Tariff. The probability of hospital admission and total annual cost of admissions were estimated in relation to age, sex, type of diabetes, history of vascular admission, HbA(1c), creatinine, body mass index and diabetes duration. RESULTS: In Scotland during 2005-2007, 24,750 people with type 1 and 195,433 people with type 2 diabetes were identified, accounting for approximately 4.3% of the total Scottish population (5.1 million). The estimated total annual cost of admissions for all people diagnosed with type 1 and type 2 diabetes was £26 million and £275 million, respectively, approximately 12% of the total Scottish inpatient expenditure (£2.4 billion). Sex, increasing age, serum creatinine, previous vascular history and HbA(1c) (the latter differentially in type 1 and type 2) were all associated with likelihood and total annual cost of admission. CONCLUSIONS/INTERPRETATION: Diabetes inpatient expenditure accounted for 12% of the total Scottish inpatient expenditure, whilst people with diabetes account for 4.3% of the population. Of the modifiable risk factors, HbA(1c) was the most important driver of cost in type 1 diabetes.

Controlling ecological bias in evidence synthesis of trials reporting on collapsed and overlapping covariate categories.

Meta-analysis of randomized controlled trials based on aggregated data is vulnerable to ecological bias if trial results are pooled over covariates that influence the outcome variable, even when the covariate does not modify the treatment effect, or is not associated with the treatment. This paper shows how, when trial results are aggregated over different levels of covariates, the within-study covariate distribution, and the effects of both covariates and treatments can be simultaneously estimated, and ecological bias reduced. Bayesian Markov chain Monte Carlo methods are used. The method is applied to a mixed treatment comparison evidence synthesis of six alternative approaches to post-stroke inpatient care. Results are compared with a model using only the stratified covariate data available, where each stratum is treated as a separate trial, and a model using fully aggregated data, where no covariate data are used.