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BACKGROUND: Telomere length is associated with risk of several age-related diseases and cancers. We aimed to investigate the extent to which telomere length might be modifiable through lifestyle and behaviour, and whether such modification has any clinical consequences. METHODS: In this population-based study, we included participants from UK Biobank who had leukocyte telomere length (LTL) measurement, ethnicity, and white blood cell count data. We investigated associations of LTL with 117 potentially modifiable traits, as well as two indices of healthy behaviours incorporating between them smoking, physical activity, diet, maintenance of a healthy bodyweight, and alcohol intake, using both available and imputed data. To help interpretation, associations were summarised as the number of equivalent years of age-related change in LTL by dividing the trait β coefficients with the age β coefficient. We used mendelian randomisation to test causality of selected associations. We investigated whether the associations of LTL with 22 diseases were modified by the number of healthy behaviours and the extent to which the associations of more healthy behaviours with greater life expectancy and lower risk of coronary artery disease might be mediated through LTL. FINDINGS: 422 797 participants were available for the analysis (227 620 [53·8%] were women and 400 036 [94·6%] were White). 71 traits showed significant (p

Supplemental Material for Practitioners’ ability to remotely develop understanding for personalised care and support planning: a thematic analysis of multiple data sources from the feasibility phase of the Dementia Personalised Care Team (D-PACT) intervention by Hannah Wheat, Sarah Griffiths, Alex Gude, Lauren Weston, Cath Quinn, Sarah Morgan-Trimmer, Tomasina M Oh, Crispin Musicha, Leanne Greene, Mike Clark, Sarah Rybczynska-Bunt and Richard Byng in Dementia

BACKGROUND: Frailty is a multidimensional syndrome of decline that affects multiple systems and predisposes to adverse health outcomes. Although chronological age is the major risk factor, inter-individual variation in risk is not fully understood. Leucocyte telomere length (LTL), a proposed marker of biological age, has been associated with risk of many diseases. We sought to determine whether LTL is associated with risk of frailty. METHODS: We utilized cross-sectional data from 441 781 UK Biobank participants (aged 40-69 years), with complete data on frailty indicators and LTL. Frailty was defined as the presence of at least three of five indicators: weaker grip strength, slower walking pace, weight loss in the past year, lower physical activity, and exhaustion in the past 2 weeks. LTL was measured using a validated qPCR method and reported as a ratio of the telomere repeat number (T) to a single-copy gene (S) (T/S ratio). Association of LTL with frailty was evaluated using adjusted (chronological age, sex, deprivation, smoking, alcohol intake, body mass index, and multimorbidity) multinomial and ordinal regression models, and results are presented as relative risk (RRR) or odds ratios (OR), respectively, alongside the 95% confidence interval (CI). Mendelian randomization (MR), using 131 genetic variants associated with LTL, was used to assess if the association of LTL with frailty was causal. RESULTS: Frail participants (4.6%) were older (median age difference (95% CI): 3 (2.5; 3.5) years, P = 2.73 × 10-33 ), more likely to be female (61%, P = 1.97 × 10-129 ), and had shorter LTL (-0.13SD vs. 0.03SD, P = 5.43 × 10-111 ) than non-frail. In adjusted analyses, both age and LTL were associated with frailty (RRR = 1.03 (95% CI: 1.02; 1.04) per year of older chronological age, P = 3.99 × 10-12 ; 1.10 (1.08; 1.11) per SD shorter LTL, P = 1.46 × 10-30 ). Within each age group (40-49, 50-59, 60-69 years), the prevalence of frailty was about 33% higher in participants with shorter (-2SD) versus longer telomeres (+2SD). MR analysis showed an association of LTL with frailty that was directionally consistent with the observational association, but not statistically significant (MR-Median: OR (95% CI): 1.08 (0.98; 1.19) per SD shorter LTL, P = 0.13). CONCLUSIONS: Inter-individual variation in LTL is associated with the risk of frailty independently of chronological age and other risk factors. Our findings provide evidence for an additional biological determinant of frailty., This research has been conducted using the UK Biobank Resource under Application Number 6077. Generation of the LTL measurements was funded by the UK Medical Research Council (MRC), Biotechnology and Biological Sciences Research Council and British Heart Foundation (BHF) through MRC grant MR/M012816/1.

Background:\ud In high-income settings, body mass index (BMI) and measures of central adiposity, such as waist-to-hip ratio (WHR) are associated with cardiometabolic risk, but evidence from low-income settings, particularly sub-Saharan Africa (SSA), is limited. We assessed whether there are differences between central and general adiposity in their associations with fasting glucose, diabetes, systolic and diastolic blood pressures and hypertension, and whether these associations differ with gender or rural/urban setting in Malawi.\ud \ud Methods:\ud We used data from a population-based study of 27 880 Malawian adults aged ≥18 years, from both rural and urban areas. We used age-standardized z-scores of the means of BMI and WHR to directly compare their associations with glycaemic and blood pressure outcomes.\ud \ud Results:\ud Mean fasting glucose and blood pressure values and odds of hypertension increased linearly across fifths of BMI and WHR, with stronger associations with BMI. For both BMI and WHR, the associations with outcomes were stronger in urban versus rural residents. The association with diabetes was stronger in women than men, whereas for blood-pressure related outcomes a stronger association was seen in men.\ud \ud Conclusions:\ud BMI is more strongly associated with cardiometabolic risk in SSA, and might be a more useful measure than WHR, in this population. The greater positive association of adiposity with cardiometabolic outcomes in urban residents (where rates of overweight/obesity are already high) highlights the particular importance of addressing obesity within urban SSA populations.

Objectives \ud To examine the accuracy of glycated haemoglobin A1c (HbA1c) in detecting type 2 diabetes and impaired fasting glucose among adults living in Malawi. \ud Design \ud A diagnostic validation study of HbA1c. Fasting plasma glucose (FPG) ≥7.0 mmol/L was the reference standard for type 2 diabetes, and FPG between 6.1 and 6.9 mmol/L as impaired fasting glucose.\ud Participants \ud 3645 adults (of whom 63% were women) recruited from two demographic surveillance study sites in urban and rural Malawi. This analysis excluded those who had a previous diagnosis of diabetes or had history of taking diabetes medication. \ud Results \ud HbA1c demonstrated excellent validity to detect FPG-defined diabetes, with an area under the receiver operating characteristic (AUROC) curve of 0.92 (95% CI 0.90 to 0.94). At HbA1c ≥6.5% (140 mg/dL), sensitivity was 78.7% and specificity was 94.0%. Subgroup AUROCs ranged from 0.86 for participants with anaemia to 0.94 for participants in urban Malawi. There were clinical and metabolic differences between participants with true diabetes versus false positives when HbA1c was ≥6.5% (140 mg/dL). \ud Conclusions \ud The findings from this study provide justification to use HbA1c to detect type 2 diabetes. As HbA1c testing is substantially less burdensome to patients than either FPG testing or oral glucose tolerance testing, it represents a useful option for expanding access to diabetes care in sub-Saharan Africa.

Background:\ud \ud The emerging burden of cardiovascular disease and diabetes in sub-Saharan Africa threatens the gains made in health by the major international effort to combat infectious diseases. There are few data on distribution of risk factors and outcomes in the region to inform an effective public health response. A comprehensive research programme is being developed aimed at accurately documenting the burden and drivers of NCDs in urban and rural Malawi; to design and test intervention strategies. The programme includes population surveys of all people aged 18 years and above, linking individuals with newly diagnosed hypertension and diabetes to healthcare and supporting clinical services. The successes, challenges and lessons learnt from the programme to date are discussed.\ud Results:\ud \ud Over 20,000 adults have been recruited in rural Karonga and urban Lilongwe. The urban population is significantly younger and wealthier than the rural population. Employed urban individuals, particularly males, give particular recruitment challenges; male participation rates were 80.3 % in the rural population and 43.6 % in urban, whilst female rates were 93.6 and 75.6 %, respectively. The study is generating high quality data on hypertension, diabetes, lipid abnormalities and risk factors.\ud Conclusions:\ud \ud It is feasible to develop large scale studies that can reliably inform the public health approach to diabetes, cardiovascular disease and other NCDs in Sub-Saharan Africa. It is essential for studies to capture both rural and urban populations to address disparities in risk factors, including age structure. Innovative approaches are needed to address the specific challenge of recruiting employed urban males.

Additional file 1: Supplementary methods, tables and figures. Table S1. Distribution of covariates in original and imputed data in adolescents in Malawi and the UK, by sex. Table S2. Distribution of covariates in original and imputed data in adults in Malawi and the UK, by sex. Table S3. Age-standardised means lipids, body mass index (BMI) and waist-hip ratio (WHR) in Malawian and UK adolescents and adults, by sex. Table S4. Age-adjusted association between quintiles of BMI and serum lipids in Malawian and UK adolescents and adults, by sex. Table S5. Age-adjusted association between quintiles of WHR and serum lipids in Malawian and UK adolescents and adults, by sex. Table S6. Adjusted association between BMI/WHR and serum lipids in Malawian and UK adolescents and adults. Table S7. Adjusted association between BMI/WHR and dyslipidaemia in Malawian and UK adolescents and adults. Figure S1. Age-standardised prevalence of overweight, obesity and central obesity in Malawian and UK adolescents and adults, by sex. Figure S2. Age-standardised prevalence of dyslipidaemia in Malawian and UK adolescents and adults, by sex. Figure S3. Adjusted association between quintiles of BMI/WHR in adolescents and adults from Malawi (a) and ALSPAC (b). Figure S4. Age-adjusted association between BMI/WHR and serum lipids in Malawi and the UK.

Additional file 1: Supplementary methods, tables and figures. Table S1. Distribution of covariates in original and imputed data in adolescents in Malawi and the UK, by sex. Table S2. Distribution of covariates in original and imputed data in adults in Malawi and the UK, by sex. Table S3. Age-standardised means lipids, body mass index (BMI) and waist-hip ratio (WHR) in Malawian and UK adolescents and adults, by sex. Table S4. Age-adjusted association between quintiles of BMI and serum lipids in Malawian and UK adolescents and adults, by sex. Table S5. Age-adjusted association between quintiles of WHR and serum lipids in Malawian and UK adolescents and adults, by sex. Table S6. Adjusted association between BMI/WHR and serum lipids in Malawian and UK adolescents and adults. Table S7. Adjusted association between BMI/WHR and dyslipidaemia in Malawian and UK adolescents and adults. Figure S1. Age-standardised prevalence of overweight, obesity and central obesity in Malawian and UK adolescents and adults, by sex. Figure S2. Age-standardised prevalence of dyslipidaemia in Malawian and UK adolescents and adults, by sex. Figure S3. Adjusted association between quintiles of BMI/WHR in adolescents and adults from Malawi (a) and ALSPAC (b). Figure S4. Age-adjusted association between BMI/WHR and serum lipids in Malawi and the UK.