P3823Body mass index or waist and hip circumference as predictors of outcome in the UK biobank

Background

Controversies exist about the relationship between body habitus and mortality, especially for patients with cardiovascular disease.

Purpose

We evaluated the relations between different anthropometric indices and mortality amongst participants with and without cardiovascular (CV) risk factors, or established CV disease (stroke, myocardial infarction and/or heart failure), enrolled in the UK Biobank.

Methods

The UK Biobank is a large prospective study which, between 2006 and 2010, enrolled 502,620 participants aged 38–73 years. Participants filled questionnaires and had a medical history recorded, physical measurements done and biological samples taken. The UK Biobank is routinely linked to national death registries and updated on a quarterly basis. Data on death were coded according to the International Classification of Diseases, 10th Revision (ICD-10). The primary end-point was all-cause mortality (ACM) across three subgroups of men and women: those with, or without, one or more CV risk factors (smoking, diabetes and/or hypertension), and those with CV disease (history of stroke, myocardial infarction and/or heart failure) at recruitment. Presence, or absence, of CV risk factors and diagnoses of CV disease were self-reported by participants at enrolment. Associations between anthropometric indices (body mass index (BMI), waist circumference (WC), waist to hip ratio (WHiR), and waist to height ratio (WHeR)) and the risk of all-cause mortality were analysed using Cox regression models.

Results

After excluding those with history of cancer at baseline (n=45,222), 453,046 participants were included (median age: 58 (interquartile range: 50 - 63) years; 53% women), of whom 150,732 had at least one CV risk factor, and 17,884 established CV disease.

During a median follow-up of 5 years, 6,319 participants died. Baseline BMI had a U-shaped relationship with ACM, with higher nadir-values for those with CV risk factors or CV disease, for both sexes (figure). WC, WHiR and WHeR (measures of central distribution of body fat) had more linear associations with ACM, regardless of CV risk factors, CV disease and sex.

Conclusions

For adults with or without CV risk factors or established CV disease, measures of central distribution of body fat are more strongly and more linearly associated with ACM than BMI. WC, or WHiR, rather than BMI, appear to be more appropriate variables for risk stratification.

The association between driving time and unhealthy lifestyles: a cross-sectional, general population study of 386 493 UK Biobank participants

BACKGROUND

Driving is a common type of sedentary behaviour; an independent risk factor for poor health. The study explores whether driving is also associated with other unhealthy lifestyle factors.

METHODS

In a cross-sectional study of UK Biobank participants, driving time was treated as an ordinal variable and other lifestyle factors dichotomized into low/high risk based on guidelines. The associations were explored using chi-square tests for trend and binary logistic regression.

RESULTS

Of the 386 493 participants who drove, 153 717 (39.8%) drove <1 h/day; 140 140 (36.3%) 1 h/day; 60 973 (15.8%) 2 h/day; and 31 663 (8.2%) ≥3 h/day. Following adjustment for potential confounders, driving ≥3 h/day was associated with being overweight/obese (OR = 1.74, 95% CI: 1.64-1.85), smoking (OR = 1.48, 95% CI: 1.37-1.63), insufficient sleep (1.70, 95% CI: 1.61-1.80), low fruit/vegetable intake (OR = 1.26, 95% CI: 1.18-1.35) and low physical activity (OR = 1.05, 95% CI: 1.00-1.11), with dose relationships for the first three, but was not associated with higher alcohol consumption (OR = 0.94, 95% CI: 0.87-1.02).

CONCLUSIONS

Sedentary behaviour, such as driving, is known to have an independent association with adverse health outcomes. It may have additional impact mediated through its effect on other aspects of lifestyle. People with long driving times are at higher risk and might benefit from targeted interventions.

Associations of dietary protein intake with bone mineral density: An observational study in 70,215 UK Biobank participants

PURPOSE

Adequate dietary protein intake is important for the maintenance of bone health; however, data in this area is ambiguous with some suggestion that high protein intake can have deleterious effects on bone health. The aim of the current study was to explore the associations of protein intake with bone mineral density (BMD).

METHODS

We used baseline data from the UK Biobank (participants aged 40-69 years) to examine the association of protein intake with BMD (measured by ultrasound). These associations were examined, in women (n = 39,066) and men (n = 31,149), after adjustment for socio-demographic and lifestyle confounders and co-morbidities.

RESULTS

Protein intake was positively and linearly associated with BMD in women (β-coefficient 0.010 [95% CI 0.005; 0.015, p < 0.0001]) and men (β-coefficient 0.008 [95% CI 0.000; 0.015, p = 0.044]); per 1.0 g/kg/day increment in protein intake, independently of socio-demographics, dietary factors and physical activity.

CONCLUSIONS

The current data have demonstrated that higher protein intakes are positively associated with BMD in both men and women. This indicates that higher protein intakes may be beneficial for both men and women.

Adiposity among 132 479 UK Biobank participants; contribution of sugar intake vs other macronutrients

Background

Policy makers are being encouraged to specifically target sugar intake in order to combat obesity. We examined the extent to which sugar, relative to other macronutrients, was associated with adiposity.

Methods

We used baseline data from UK Biobank to examine the associations between energy intake (total and individual macronutrients) and adiposity [body mass index (BMI), percentage body fat and waist circumference]. Linear regression models were conducted univariately and adjusted for age, sex, ethnicity and physical activity.

Results

Among 132 479 participants, 66.3% of men and 51.8% of women were overweight/obese. There was a weak correlation (r = 0.24) between energy from sugar and fat; 13% of those in the highest quintile for sugar were in the lowest for fat, and vice versa. Compared with normal BMI, obese participants had 11.5% higher total energy intake and 14.6%, 13.8%, 9.5% and 4.7% higher intake from fat, protein, starch and sugar, respectively. Hence, the proportion of energy derived from fat was higher (34.3% vs 33.4%, P < 0.001) but from sugar was lower (22.0% vs 23.4%, P < 0.001). BMI was more strongly associated with total energy [coefficient 2.47, 95% confidence interval (CI) 2.36-2.55] and energy from fat (coefficient 1.96, 95% CI 1.91-2.06) than sugar (coefficient 0.48, 95% CI 0.41-0.55). The latter became negative after adjustment for total energy.

Conclusions

Fat is the largest contributor to overall energy. The proportion of energy from fat in the diet, but not sugar, is higher among overweight/obese individuals. Focusing public health messages on sugar may mislead on the need to reduce fat and overall energy consumption.

Association between grip strength and diabetes prevalence in black, South-Asian, and white European ethnic groups: a cross-sectional analysis of 418 656 participants in the UK Biobank study

AIMS

To quantify the extent to which ethnic differences in muscular strength might account for the substantially higher prevalence of diabetes in black and South-Asian compared with white European adults.

METHODS

This cross-sectional study used baseline data from the UK Biobank study on 418 656 white European, black and South-Asian participants, aged 40-69 years, who had complete data on diabetes status and hand-grip strength. Associations between hand-grip strength and diabetes were assessed using logistic regression and were adjusted for potential confounding factors.

RESULTS

Lower grip strength was associated with higher prevalence of diabetes, independent of confounding factors, across all ethnicities in both men and women. Diabetes prevalence was approximately three- to fourfold higher in South-Asian and two- to threefold higher in black participants compared with white European participants across all levels of grip strength, but grip strength in South-Asian men and women was ~ 5-6 kg lower than in the other ethnic groups. Thus, the attributable risk for diabetes associated with low grip strength was substantially higher in South-Asian participants (3.9 and 4.2 cases per 100 men and women, respectively) than in white participants (2.0 and 0.6 cases per 100 men and women, respectively). Attributable risk associated with low grip strength was also high in black men (4.3 cases) but not in black women (0.4 cases).

CONCLUSIONS

Low strength is associated with a disproportionately large number of diabetes cases in South-Asian men and women and in black men. Trials are needed to determine whether interventions to improve strength in these groups could help reduce ethnic inequalities in diabetes prevalence.

Dietary fat and total energy intake modifies the association of genetic profile risk score on obesity: evidence from 48 170 UK Biobank participants

BACKGROUND

Obesity is a multifactorial condition influenced by both genetics and lifestyle. The aim of this study was to investigate whether the association between a validated genetic profile risk score for obesity (GPRS-obesity) and body mass index (BMI) or waist circumference (WC) was modified by macronutrient intake in a large general population study.

METHODS

This study included cross-sectional data from 48 170 white European adults, aged 37-73 years, participating in the UK Biobank. Interactions between GPRS-obesity and macronutrient intake (including total energy, protein, fat, carbohydrate and dietary fibre intake) and its effects on BMI and WC were investigated.

RESULTS

The 93-single-nucleotide polymorphism (SNP) GPRS was associated with a higher BMI (β: 0.57 kg m^-2 per s.d. increase in GPRS (95% confidence interval: 0.53-0.60); P=1.9 × 10^-183) independent of major confounding factors. There was a significant interaction between GPRS and total fat intake (P_{(interaction)}=0.007). Among high-fat-intake individuals, BMI was higher by 0.60 (0.52, 0.67) kg m^-2 per s.d. increase in GPRS-obesity; the change in BMI with GPRS was lower among low-fat-intake individuals (β: 0.50 (0.44, 0.57) kg m^-2). Significant interactions with similar patterns were observed for saturated fat intake (high β: 0.66 (0.59, 0.73) versus low β: 0.49 (0.42, 0.55) kg m^-2, P_{(interaction)}=2 × 10^-4) and for total energy intake (high β: 0.58 (0.51, 0.64) versus low β: 0.49 (0.42, 0.56) kg m^-2, P_{(interaction)}=0.019), but not for protein intake, carbohydrate intake and fibre intake (P_{(interaction)} >0.05). The findings were broadly similar using WC as the outcome.

CONCLUSIONS

These data suggest that the benefits of reducing the intake of fats and total energy intake may be more important in individuals with high genetic risk for obesity.