Search

Background: Disparities in type 2 diabetes (T2D) care provision and clinical outcomes have been reported in the last 2 decades in the UK. Since then, a number of initiatives have attempted to address this imbalance. The aim was to evaluate contemporary data as to whether disparities exist in glycaemic control, monitoring, and prescribing in people with T2D.Methods and Findings: A T2D cohort was identified from the Royal College of General Practitioners Research and Surveillance Centre dataset: a nationally representative sample of 164 primary care practices (general practices) across England. Diabetes healthcare provision and glucose-lowering medication use between 1 January 2012 and 31 December 2016 were studied. Healthcare provision included annual HbA1c, renal function (estimated glomerular filtration rate [eGFR]), blood pressure (BP), retinopathy, and neuropathy testing. Variables potentially associated with disparity outcomes were assessed using mixed effects logistic and linear regression, adjusted for age, sex, ethnicity, and socioeconomic status (SES) using the Index of Multiple Deprivation (IMD), and nested using random effects within general practices. Ethnicity was defined using the Office for National Statistics ethnicity categories: White, Mixed, Asian, Black, and Other (including Arab people and other groups not classified elsewhere). From the primary care adult population (n = 1,238,909), we identified a cohort of 84,452 (5.29%) adults with T2D. The mean age of people with T2D in the included cohort at 31 December 2016 was 68.7 ± 12.6 years; 21,656 (43.9%) were female. The mean body mass index was 30.7 ± SD 6.4 kg/m2. The most deprived groups (IMD quintiles 1 and 2) showed poorer HbA1c than the least deprived (IMD quintile 5). People of Black ethnicity had worse HbA1c than those of White ethnicity. Asian individuals were less likely than White individuals to be prescribed insulin (odds ratio [OR] 0.86, 95% CI 0.79-0.95; p < 0.01), sodium-glucose cotransporter-2 (SGLT2) inhibitors (OR 0.68, 95% CI 0.58-0.79; p < 0.001), and glucagon-like peptide-1 (GLP-1) agonists (OR 0.37, 95% CI 0.31-0.44; p < 0.001). Black individuals were less likely than White individuals to be prescribed SGLT2 inhibitors (OR 0.50, 95% CI 0.39-0.65; p < 0.001) and GLP-1 agonists (OR 0.45, 95% CI 0.35-0.57; p < 0.001). Individuals in IMD quintile 5 were more likely than those in the other IMD quintiles to have annual testing for HbA1c, BP, eGFR, retinopathy, and neuropathy. Black individuals were less likely than White individuals to have annual testing for HbA1c (OR 0.89, 95% CI 0.79-0.99; p = 0.04) and retinopathy (OR 0.82, 95% CI 0.70-0.96; p = 0.011). Asian individuals were more likely than White individuals to have monitoring for HbA1c (OR 1.10, 95% CI 1.01-1.20; p = 0.023) and eGFR (OR 1.09, 95% CI 1.00-1.19; p = 0.048), but less likely for retinopathy (OR 0.88, 95% CI 0.79-0.97; p = 0.01) and neuropathy (OR 0.88, 95% CI 0.80-0.97; p = 0.01). The study is limited by the nature of being observational and defined using retrospectively collected data. Disparities in diabetes care may show regional variation, which was not part of this evaluation.Conclusions: Our findings suggest that disparity in glycaemic control, diabetes-related monitoring, and prescription of newer therapies remains a challenge in diabetes care. Both SES and ethnicity were important determinants of inequality. Disparities in glycaemic control and other areas of care may lead to higher rates of complications and adverse outcomes for some groups. [ABSTRACT FROM AUTHOR]

Background: Diabetes mellitus (DM) increases the risk of adverse maternal and neonatal outcomes, and optimization of glycemic control during pregnancy can help mitigate risks associated with diabetes. However, studies seldom focus precisely on maternal blood glucose level prior to pregnancy. We aimed to evaluate the associations between preconception blood fasting plasma glucose (FPG) level and subsequent pregnancy outcomes.Methods and Findings: We conducted a population-based retrospective cohort study among 6,447,339 women aged 20-49 years old who participated in National Free Pre-Pregnancy Checkups Project and completed pregnancy outcomes follow-up between 2010 and 2016 in China. During the preconception health examination, serum FPG concentration was measured, and self-reported history of DM was collected. Women were classified into three groups (normal FPG group: FPG < 5.6 mmol/L and no self-reported history of DM; impaired fasting glucose [IFG]: FPG 5.6-6.9 mmol/L and no self-reported history of DM; and DM: FPG ≥ 7.0 mmol/L or self-reported history of DM). The primary outcomes were adverse pregnancy outcomes, including spontaneous abortion, preterm birth (PTB), macrosomia, small for gestational age infant (SGA), birth defect, and perinatal infant death. Logistic regression model was used to calculate odds ratio (OR) and 95% confidence interval (CI) after adjusting for confounding variables. The mean age of women was 25.24 years, 91.47% were of Han nationality, and 92.85% were from rural areas. The incidence of DM and IFG was 1.18% (76,297) and 13.15% (847,737), respectively. Only 917 (1.20%) women reported a history of DM (awareness of their DM status), of whom 37.28% (337) had an elevated preconception FPG level (≥ 5.6 mmol/L), regarded as noncontrolled DM. A total of 1,005,568 (15.60%) women had adverse pregnancy outcomes. Compared with women with normal FPG, women with IFG had higher risks of spontaneous abortion (OR 1.08; 95% CI 1.06-1.09; P < 0.001), PTB (1.02; 1.01-1.03; P < 0.001), macrosomia (1.07; 1.06-1.08; P < 0.001), SGA (1.06; 1.02-1.10; P = 0.007), and perinatal infant death (1.08; 1.03-1.12; P < 0.001); the corresponding ORs for women with DM were 1.11 (95% CI 1.07-1.15; P < 0.001), 1.17 (1.14-1.20; P < 0.001), 1.13 (1.09-1.16; P < 0.001), 1.17 (1.04-1.32; P = 0.008), and 1.59 (1.44-1.76; P < 0.001). Women with DM also had a higher risk of birth defect (OR 1.42; 95% CI 1.15-1.91; P = 0.002). Among women without self-reported history of DM, there was a positive linear association between FPG levels and spontaneous abortion, PTB, macrosomia, SGA, and perinatal infant death (P for trend <0.001, <0.001, <0.001, 0.001, <0.001). Information about hypoglycemic medication before or during pregnancy was not collected, and we cannot adjust it in the analysis, which could result in underestimation of risks. Data on 2-hour plasma glucose level and HbA1c concentration were not available, and the glycemic control status was evaluated according to FPG value in women with DM.Conclusions: Women with preconception IFG or DM had higher risk of adverse pregnancy outcomes, including spontaneous abortion, PTB, macrosomia, SGA, and perinatal infant death. Preconception glycemic control through appropriate methods is one of the most important aspects of preconception care and should not be ignored by policy makers. [ABSTRACT FROM AUTHOR]

Background: Asians are predisposed to a lean heart failure (HF) phenotype. Data on the 'obesity paradox', reported in Western populations, are scarce in Asia and have only utilised the traditional classification of body mass index (BMI). We aimed to investigate the association between obesity (defined by BMI and abdominal measures) and HF outcomes in Asia.Methods and Findings: Utilising the Asian Sudden Cardiac Death in Heart Failure (ASIAN-HF) registry (11 Asian regions including Taiwan, Hong Kong, China, India, Malaysia, Thailand, Singapore, Indonesia, Philippines, Japan, and Korea; 46 centres with enrolment between 1 October 2012 and 6 October 2016), we prospectively examined 5,964 patients with symptomatic HF (mean age 61.3 ± 13.3 years, 26% women, mean BMI 25.3 ± 5.3 kg/m2, 16% with HF with preserved ejection fraction [HFpEF; ejection fraction ≥ 50%]), among whom 2,051 also had waist-to-height ratio (WHtR) measurements (mean age 60.8 ± 12.9 years, 24% women, mean BMI 25.0 ± 5.2 kg/m2, 7% HFpEF). Patients were categorised by BMI quartiles or WHtR quartiles or 4 combined groups of BMI (low, <24.5 kg/m2 [lean], or high, ≥24.5 kg/m2 [obese]) and WHtR (low, <0.55 [thin], or high, ≥0.55 [fat]). Cox proportional hazards models were used to examine a 1-year composite outcome (HF hospitalisation or mortality). Across BMI quartiles, higher BMI was associated with lower risk of the composite outcome (ptrend < 0.001). Contrastingly, higher WHtR was associated with higher risk of the composite outcome. Individuals in the lean-fat group, with low BMI and high WHtR (13.9%), were more likely to be women (35.4%) and to be from low-income countries (47.7%) (predominantly in South/Southeast Asia), and had higher prevalence of diabetes (46%), worse quality of life scores (63.3 ± 24.2), and a higher rate of the composite outcome (51/232; 22%), compared to the other groups (p < 0.05 for all). Following multivariable adjustment, the lean-fat group had higher adjusted risk of the composite outcome (hazard ratio 1.93, 95% CI 1.17-3.18, p = 0.01), compared to the obese-thin group, with high BMI and low WHtR. Results were consistent across both HF subtypes (HFpEF and HF with reduced ejection fraction [HFrEF]; pinteraction = 0.355). Selection bias and residual confounding are potential limitations of such multinational observational registries.Conclusions: In this cohort of Asian patients with HF, the 'obesity paradox' is observed only when defined using BMI, with WHtR showing the opposite association with the composite outcome. Lean-fat patients, with high WHtR and low BMI, have the worst outcomes. A direct correlation between high WHtR and the composite outcome is apparent in both HFpEF and HFrEF.Trial Registration: Asian Sudden Cardiac Death in HF (ASIAN-HF) Registry ClinicalTrials.gov Identifier: NCT01633398. [ABSTRACT FROM AUTHOR]

Background: Despite dietary recommendations of polyunsaturated fatty acids (PUFAs) for cardiometabolic health, n-3 and n-6 PUFAs and their interplay in relation to diabetes risk remain debated. Importantly, data among pregnant women are scarce. We investigated individual plasma phospholipid n-3 and n-6 PUFAs in early to midpregnancy in relation to subsequent risk of gestational diabetes mellitus (GDM).Methods and Findings: Within the National Institute of Child Health and Human Development (NICHD) Fetal Growth Studies-Singleton Cohort (n = 2,802), individual plasma phospholipid n-3 and n-6 PUFAs levels were measured at gestational weeks (GWs) 10-14, 15-26, 23-31, and 33-39 among 107 GDM cases (ascertained on average at GW 27) and 214 non-GDM controls. Conditional logistic regression was used, adjusting for major risk factors for GDM. After adjusting for covariates, individual n-3 eicosapentaenoic acid (EPA), docosapentaenoic acid (DPA), and docosahexaenoic acid (DHA) were inversely correlated with insulin-resistance markers, whereas individual n-6 dihomo-gamma-linolenic acid (DGLA) was positively correlated with insulin-resistance markers. At GW 15-26, a standard deviation (SD) increase in total n-3 PUFAs and individual n-3 DPA was associated with a 36% (adjusted odds ratio 0.64; 95% CI 0.42-0.96; P = 0.042) and 33% (0.67; 95% CI 0.45-0.99; P = 0.047) lower risk of GDM, respectively; however, the significance did not persist after post hoc false-discovery rate (FDR) correction (FDR-corrected P values > 0.05). Associations between total n-6 PUFAs and GDM were null, whereas associations with individual n-6 PUFAs were differential. Per SD increase, gamma-linolenic acid (GLA) at GWs 10-14 and DGLA at GWs 10-14 and 15-26 were significantly associated with a 1.40- to 1.95-fold higher risk of GDM, whereas docosatetraenoic acid (DTA) at GW 15-26 was associated with a 45% (0.55; 95% CI 0.37-0.83) lower risk of GDM (all FDR-corrected P values < 0.05). Null associations were observed for linoleic acid (LA) in either gestational window in relation to risk of GDM. Women with high (≥median) n-3 PUFAs and low (Conclusions: Our findings may suggest a potential role of primarily endogenously metabolized plasma phospholipid n-6 PUFAs including GLA, DGLA, and DTA in early to midpregnancy in the development of GDM. Null findings on primarily diet-derived n-3 EPA and DHA and n-6 LA do not provide strong evidence to suggest a beneficial role in prevention of GDM, although not excluding the potential benefit of EPA and DHA on glucose-insulin homeostasis given the inverse associations with insulin-resistance markers. Our findings highlight the importance of assessing individual circulating PUFAs to investigate their distinct pathophysiologic roles in glucose homeostasis in pregnancy. [ABSTRACT FROM AUTHOR]

Background: The inflammatory contribution to type 2 diabetes (T2D) has suggested new therapeutic targets using biologic drugs designed for rheumatoid arthritis (RA). On this basis, we aimed at investigating whether interleukin-1 (IL-1) inhibition with anakinra, a recombinant human IL-1 receptor antagonist, could improve both glycaemic and inflammatory parameters in participants with RA and T2D compared with tumour necrosis factor (TNF) inhibitors (TNFis).Methods and Findings: This study, designed as a multicentre, open-label, randomised controlled trial, enrolled participants, followed up for 6 months, with RA and T2D in 12 Italian rheumatologic units between 2013 and 2016. Participants were randomised to anakinra or to a TNFi (i.e., adalimumab, certolizumab pegol, etanercept, infliximab, or golimumab), and the primary end point was the change in percentage of glycated haemoglobin (HbA1c%) (EudraCT: 2012-005370-62 ClinicalTrial.gov: NCT02236481). In total, 41 participants with RA and T2D were randomised, and 39 eligible participants were treated (age 62.72 ± 9.97 years, 74.4% female sex). The majority of participants had seropositive RA disease (rheumatoid factor and/or anticyclic citrullinated peptide antibody [ACPA] 70.2%) with active disease (Disease Activity Score-28 [DAS28]: 5.54 ± 1.03; C-reactive protein 11.84 ± 9.67 mg/L, respectively). All participants had T2D (HbA1c%: 7.77 ± 0.70, fasting plasma glucose: 139.13 ± 42.17 mg). When all the enrolled participants reached 6 months of follow-up, the important crude difference in the main end point, confirmed by an unplanned ad interim analysis showing the significant effects of anakinra, which were not observed in the other group, led to the study being stopped for early benefit. Participants in the anakinra group had a significant reduction of HbA1c%, in an unadjusted linear mixed model, after 3 months (β: -0.85, p < 0.001, 95% CI -1.28 to -0.42) and 6 months (β: -1.05, p < 0.001, 95% CI -1.50 to -0.59). Similar results were observed adjusting the model for relevant RA and T2D clinical confounders (male sex, age, ACPA positivity, use of corticosteroids, RA duration, T2D duration, use of oral antidiabetic drug, body mass index [BMI]) after 3 months (β: -1.04, p < 0.001, 95% CI -1.52 to -0.55) and 6 months (β: -1.24, p < 0.001, 95% CI -1.75 to -0.72). Participants in the TNFi group had a nonsignificant slight decrease of HbA1c%. Assuming the success threshold to be HbA1c% ≤ 7, we considered an absolute risk reduction (ARR) = 0.42 (experimental event rate = 0.54, control event rate = 0.12); thus, we estimated, rounding up, a number needed to treat (NNT) = 3. Concerning RA, a progressive reduction of disease activity was observed in both groups. No severe adverse events, hypoglycaemic episodes, or deaths were observed. Urticarial lesions at the injection site led to discontinuation in 4 (18%) anakinra-treated participants. Additionally, we observed nonsevere infections, including influenza, nasopharyngitis, upper respiratory tract infection, urinary tract infection, and diarrhoea in both groups. Our study has some limitations, including open-label design and previously unplanned ad interim analysis, small size, lack of some laboratory evaluations, and ongoing use of other drugs.Conclusions: In this study, we observed an apparent benefit of IL-1 inhibition in participants with RA and T2D, reaching the therapeutic targets of both diseases. Our results suggest the concept that IL-1 inhibition may be considered a targeted treatment for RA and T2D.Trial Registration: The trial is registered with EU Clinical Trials Register, EudraCT Number: 2012-005370-62 and with ClinicalTrial.gov, number NCT02236481. [ABSTRACT FROM AUTHOR]

Background: The Developmental Origins of Health and Disease (DOHaD) hypothesis postulates that exposures during early life, such as maternal dietary intake during pregnancy, may have a lifelong impact on the individual's susceptibility to diseases. The individual's own lifestyle habits are obviously an additional factor, but we have only limited knowledge regarding how it may interact with prenatal exposures in determining later disease. To gain further insight into these potentially complex relationships, we examined the longitudinal association between maternal diet quality during pregnancy and diet quality in early adolescence in a contemporary cohort.Methods and Findings: From 1996 to 2003, the Danish National Birth Cohort (DNBC) was established. Women from across the country were enrolled, and dietary intake in midpregnancy was assessed concurrently with a 360-item food frequency questionnaire (FFQ) (https://www.dnbc.dk/-/media/arkiv/projekt-sites/dnbc/kodeboeger/dnbc-food-frequency-questionnaire/dnbc-food-frequency-questionnaire-pdf.pdf?la=en). During 2013-2018, dietary intake was assessed at age 14 years with a 150-item FFQ (https://www.dnbc.dk/-/media/arkiv/projekt-sites/dnbc/kodeboeger/ffq-14/dnbc-ffq-14-english-translation.pdf?la=en) in the DNBC children. Among the 19,582 mother-offspring pairs included in the analyses, the mean age (±standard deviation [SD]) was 30.7 (±4.1) years and 14.0 (±0.0) years for mothers and offspring, respectively. The majority of both mothers (67%) and offspring (76%) were classified as normal weight. For both questionnaires, a Healthy Eating Index (HEI) was developed as an indicator for diet quality based on current Danish Food-Based Dietary Guidelines (FBDG) including eight components: fruits and vegetables, fish, dietary fibres, red meat, saturated fatty acids (SFAs), sodium, sugar-sweetened beverages (SSBs), and added sugar. The HEI score was divided into quartiles; individuals in the highest quartile represented those with the most optimal diet. The maternal HEI score was correlated positively with offspring HEI score (Pearson r = 0.22, p < 0.001). A log-linear binomial model was used to estimate the relative risk of the offspring being in the highest quartile of HEI at age 14 years if the mother was ranked in quartile 4 during pregnancy. Results showed that offspring born to mothers who were in the highest HEI quartile during pregnancy were more likely themselves to be located in the highest HEI quartile at age 14 years (risk ratio [RR]: 2.1, 95% confidence interval [CI]: 2.0, 2.3, p < 0.001). Adjusting for maternal prepregnancy body mass index (BMI), parity, education, alcohol intake, physical activity, smoking, and breastfeeding, as well as offspring total energy intake and sex, did not influence the effect estimates. The limitations of our study include that some attrition bias towards more healthy participants was observed when comparing participants with nonparticipants. Bias in the FFQ method may also have resulted in underrepresentation of adolescents with poorer diet quality.Conclusions: In this study using data from a large national birth cohort, we observed that maternal diet quality during pregnancy was associated with diet quality of the offspring at age 14 years. These findings indicate the importance of separating early dietary exposures from later dietary exposures when studying dietary aetiologies of diseases postulated to have developmental origins such as, for instance, obesity or asthma in observational settings. [ABSTRACT FROM AUTHOR]

Background: Global data indicate that women with a history of hyperglycemia first detected in pregnancy (HFDP) are at up to 7 times risk of progressing to type 2 diabetes mellitus (T2DM) compared with their counterparts who have pregnancies that are not complicated by hyperglycemia. However, there are no data from the sub-Saharan African region, which has the highest projected rise in diabetes prevalence globally. The aim of this study was to determine the proportion of women who progress to T2DM and associated risk factors 5 to 6 years after HFDP in Cape Town, South Africa.Methods and Findings: All women with HFDP, at a major referral hospital in Cape Town, were followed up 5 to 6 years later using a cross-sectional study. Each participant had a 75 g oral glucose tolerance test; anthropometric measurements and a survey were administered. A total of 220 participants were followed up. At this time, their mean age was 37.2 years (SD 6.0). Forty-eight percent (95% CI 41.2-54.4) progressed to T2DM, 5.5% (95% CI 3.1-9.4) had impaired fasting glucose, and 10.5% (95% CI 7.0-15.3) had impaired glucose tolerance. Of the participants who progressed to T2DM, 47% were unaware of their diabetes status. When HFDP was categorized post hoc according to WHO 2013 guidelines, progression in the diabetes in pregnancy (DIP) group was 81% (95% CI 70.2-89.0) and 31.3% (95% CI 24.4-39.3) in the gestational diabetes mellitus (GDM) category. Factors associated with risk of progression to T2DM were; at follow-up: waist circumference (odds ratios [OR] 1.1, 95% CI 1.0-1.1, p = 0.007), hip circumference (OR 0.9, 95% CI 0.8-1.0, p = 0.001), and BMI (OR 1.1, 95% CI 1.0-1.3, p = 0.001), and at baseline: insulin (OR 25.8, 95% CI 3.9-171.4, p = 0.001) and oral hypoglycaemic treatment during HFDP (OR 4.1, 95% CI 1.3-12.9, p = 0.018), fasting (OR 2.7, 95% CI 1.5-4.8, p = 0.001), and oral glucose tolerance test 2-hour glucose concentration at HFDP diagnosis (OR 4.3, 95% CI 2.4-7.7, p < 0.001). Our findings have limitations in that we did not include a control group of women without a history of HFDP.Conclusions: The progression to T2DM in women with previous HFDP found in this study highlights the need for interventions to delay or prevent progression to T2DM after HFDP. In addition, interventions to prevent HFDP may also contribute to reducing the risk of T2DM. [ABSTRACT FROM AUTHOR]

Background: One in 5 women experience mental illness in pregnancy or post partum. Universal preventive interventions have not lowered the incidence of perinatal mental illness, perhaps because those at highest risk were not targeted. Outside of pregnancy, chronic physical conditions are known to confer increased risk for mental illness. Our objective was to examine the association between chronic physical conditions and risk of perinatal mental illness.Methods and Findings: We conducted a population-based retrospective cohort study using linked health administrative data sets in Ontario, Canada, in 2005 to 2015. We compared 77,385 women with chronic physical conditions to 780,619 women without such conditions, all of whom had a singleton live birth. Excluded were women with a mental illness diagnosis within 2 years before pregnancy. Chronic physical conditions were captured using the Agency for Healthcare Research and Quality Chronic Condition Indicator, applied to acute healthcare encounters in the 2 years before pregnancy. The outcome was perinatal mental illness, defined by a mental illness or addiction diagnosis arising between conception and 365 days post partum. The outcome was further defined by timing (prenatal or post partum) and specific diagnosis (psychotic disorder, mood or anxiety disorder, substance use disorder, self-harm, or other). Modified Poisson regression generated relative risks and 95% confidence intervals (CIs), adjusted for age, parity, rural residence, income quintile, and remote history of mental health care. Women in the cohort had an average age of 29.6 years (standard deviation 5.4), 44.2% were primiparous, 11.0% lived in a rural area, 40.1% were in the lowest 2 income quintiles, and 47.9% had a remote history of mental health care. More women with (20.4%) than without (15.6%) a chronic physical condition experienced perinatal mental illness-an adjusted relative risk (aRR) of 1.20 (95% CI 1.18-1.22, p < 0.0001). The aRRs were statistically significant for mental illness in pregnancy (1.12, 95% CI 1.10-1.15, p < 0.0001) and post partum (1.25, 95% CI 1.23-1.28, p < 0.0001). Psychotic disorders (aRR 1.50, 95% CI 1.36-1.65, p < 0.0001), mood or anxiety disorders (aRR 1.19, 95% CI 1.17-1.21, p < 0.0001), substance use disorders (aRR 1.47, 95% CI 1.34-1.62, p < 0.0001), and other mental illness (aRR 1.68, 95% CI 1.50-1.87, p < 0.0001) were more likely in women with than without chronic physical conditions, but not self-harm (aRR 1.14, 95% CI 0.87-1.48, p = 0.34). The study was limited by reliance on acute health care encounters to measure chronic physical conditions and the inability to capture undiagnosed mental health problems.Conclusions: Findings from this study suggest that women with a chronic physical condition predating pregnancy may be at heightened risk of developing mental illness in the perinatal period. These women may require targeted efforts to lower the severity of their condition and improve their coping strategies and supports in pregnancy and thereafter. [ABSTRACT FROM AUTHOR]

Background: Metformin is increasingly offered as an acceptable and economic alternative to insulin for treatment of gestational diabetes mellitus (GDM) in many countries. However, the impact of maternal metformin treatment on the trajectory of fetal, infant, and childhood growth is unknown.Methods and Findings: PubMed, Ovid Embase, Medline, Web of Science, ClinicalTrials.gov, and the Cochrane database were systematically searched (from database inception to 26 February 2019). Outcomes of GDM-affected pregnancies randomised to treatment with metformin versus insulin were included (randomised controlled trials and prospective randomised controlled studies) from cohorts including European, American, Asian, Australian, and African women. Studies including pregnant women with pre-existing diabetes or non-diabetic women were excluded, as were trials comparing metformin treatment with oral glucose-lowering agents other than insulin. Two reviewers independently assessed articles for eligibility and risk of bias, and conflicts were resolved by a third reviewer. Outcome measures were parameters of fetal, infant, and childhood growth, including weight, height, BMI, and body composition. In total, 28 studies (n = 3,976 participants) met eligibility criteria and were included in the meta-analysis. No studies reported fetal growth parameters; 19 studies (n = 3,723 neonates) reported measures of neonatal growth. Neonates born to metformin-treated mothers had lower birth weights (mean difference -107.7 g, 95% CI -182.3 to -32.7, I2 = 83%, p = 0.005) and lower ponderal indices (mean difference -0.13 kg/m3, 95% CI -0.26 to 0.00, I2 = 0%, p = 0.04) than neonates of insulin-treated mothers. The odds of macrosomia (odds ratio [OR] 0.59, 95% CI 0.46 to 0.77, p < 0.001) and large for gestational age (OR 0.78, 95% CI 0.62 to 0.99, p = 0.04) were lower following maternal treatment with metformin compared to insulin. There was no difference in neonatal height or incidence of small for gestational age between groups. Two studies (n = 411 infants) reported measures of infant growth (18-24 months of age). In contrast to the neonatal phase, metformin-exposed infants were significantly heavier than those in the insulin-exposed group (mean difference 440 g, 95% CI 50 to 830, I2 = 4%, p = 0.03). Three studies (n = 520 children) reported mid-childhood growth parameters (5-9 years). In mid-childhood, BMI was significantly higher (mean difference 0.78 kg/m2, 95% CI 0.23 to 1.33, I2 = 7%, p = 0.005) following metformin exposure than following insulin exposure, although the difference in absolute weights between the groups was not significantly different (p = 0.09). Limited evidence (1 study with data treated as 2 cohorts) suggested that adiposity indices (abdominal [p = 0.02] and visceral [p = 0.03] fat volumes) may be higher in children born to metformin-treated compared to insulin-treated mothers. Study limitations include heterogeneity in metformin dosing, heterogeneity in diagnostic criteria for GDM, and the scarcity of reporting of childhood outcomes.Conclusions: Following intrauterine exposure to metformin for treatment of maternal GDM, neonates are significantly smaller than neonates whose mothers were treated with insulin during pregnancy. Despite lower average birth weight, metformin-exposed children appear to experience accelerated postnatal growth, resulting in heavier infants and higher BMI by mid-childhood compared to children whose mothers were treated with insulin. Such patterns of low birth weight and postnatal catch-up growth have been reported to be associated with adverse long-term cardio-metabolic outcomes. This suggests a need for further studies examining longitudinal perinatal and childhood outcomes following intrauterine metformin exposure. This review protocol was registered with PROSPERO under registration number CRD42018117503. [ABSTRACT FROM AUTHOR]

Background: Preeclampsia has been suggested to increase the risk of end-stage kidney disease (ESKD); however, most studies were unable to adjust for potential confounders including pre-existing comorbidities such as renal disease and cardiovascular disease (CVD). We aimed to examine the association between preeclampsia and the risk of ESKD in healthy women, while taking into account pre-existing comorbidity and potential confounders.Methods and Findings: Using data from the Swedish Medical Birth Register (MBR), women who had singleton live births in Sweden between 1982 and 2012, including those who had preeclampsia, were identified. Women with a diagnosis of chronic kidney disease (CKD), CVD, hypertension, or diabetes prior to the first pregnancy were excluded. The outcome was a diagnosis of ESKD, identified from the Swedish Renal Registry (SRR) from January 1, 1991, onwards along with the specified cause of renal disease. We conducted Cox proportional hazards regression analysis to examine the association between preeclampsia and ESKD adjusting for several potential confounders: maternal age, body mass index (BMI), education, native country, and smoking. This analysis accounts for differential follow-up among women because women had different lengths of follow-up time. We performed subgroup analyses according to preterm preeclampsia, small for gestational age (SGA), and women who had 2 pregnancies with preeclampsia in both. The cohort consisted of 1,366,441 healthy women who had 2,665,320 singleton live births in Sweden between 1982 and 2012. At the first pregnancy, women's mean (SD) age and BMI were 27.8 (5.13) and 23.4 (4.03), respectively, 15.2% were smokers, and 80.7% were native Swedish. The overall median (interquartile range [IQR]) follow-up was 7.4 years (3.2-17.4) and 16.4 years (10.3-22.0) among women with ESKD diagnosis. During the study period, 67,273 (4.9%) women having 74,648 (2.8% of all pregnancies) singleton live births had preeclampsia, and 410 women developed ESKD with an incidence rate of 1.85 per 100,000 person-years. There was an association between preeclampsia and ESKD in the unadjusted analysis (hazard ratio [HR] = 4.99, 95% confidence interval [CI] 3.93-6.33; p < 0.001), which remained in the extensively adjusted (HR = 4.96, 95% CI 3.89-6.32, p < 0.001) models. Women who had preterm preeclampsia (adjusted HR = 9.19; 95% CI 5.16-15.61, p < 0.001) and women who had preeclampsia in 2 pregnancies (adjusted HR = 7.13, 95% CI 3.12-16.31, p < 0.001) had the highest risk of ESKD compared with women with no preeclampsia. Considering this was an observational cohort study, and although we accounted for several potential confounders, residual confounding cannot be ruled out.Conclusions: The present findings suggest that women with preeclampsia and no major comorbidities before their first pregnancy are at a 5-fold increased risk of ESKD compared with parous women with no preeclampsia; however, the absolute risk of ESKD among women with preeclampsia remains small. Preeclampsia should be considered as an important risk factor for subsequent ESKD. Whether screening and/or preventive strategies will reduce the risk of ESKD in women with adverse pregnancy outcomes is worthy of further investigation. [ABSTRACT FROM AUTHOR]

Background: With no effective treatments for cognitive decline or dementia, improving the evidence base for modifiable risk factors is a research priority. This study investigated associations between risk factors and late-life cognitive decline on a global scale, including comparisons between ethno-regional groups.Methods and Findings: We harmonized longitudinal data from 20 population-based cohorts from 15 countries over 5 continents, including 48,522 individuals (58.4% women) aged 54-105 (mean = 72.7) years and without dementia at baseline. Studies had 2-15 years of follow-up. The risk factors investigated were age, sex, education, alcohol consumption, anxiety, apolipoprotein E ε4 allele (APOE*4) status, atrial fibrillation, blood pressure and pulse pressure, body mass index, cardiovascular disease, depression, diabetes, self-rated health, high cholesterol, hypertension, peripheral vascular disease, physical activity, smoking, and history of stroke. Associations with risk factors were determined for a global cognitive composite outcome (memory, language, processing speed, and executive functioning tests) and Mini-Mental State Examination score. Individual participant data meta-analyses of multivariable linear mixed model results pooled across cohorts revealed that for at least 1 cognitive outcome, age (B = -0.1, SE = 0.01), APOE*4 carriage (B = -0.31, SE = 0.11), depression (B = -0.11, SE = 0.06), diabetes (B = -0.23, SE = 0.10), current smoking (B = -0.20, SE = 0.08), and history of stroke (B = -0.22, SE = 0.09) were independently associated with poorer cognitive performance (p < 0.05 for all), and higher levels of education (B = 0.12, SE = 0.02) and vigorous physical activity (B = 0.17, SE = 0.06) were associated with better performance (p < 0.01 for both). Age (B = -0.07, SE = 0.01), APOE*4 carriage (B = -0.41, SE = 0.18), and diabetes (B = -0.18, SE = 0.10) were independently associated with faster cognitive decline (p < 0.05 for all). Different effects between Asian people and white people included stronger associations for Asian people between ever smoking and poorer cognition (group by risk factor interaction: B = -0.24, SE = 0.12), and between diabetes and cognitive decline (B = -0.66, SE = 0.27; p < 0.05 for both). Limitations of our study include a loss or distortion of risk factor data with harmonization, and not investigating factors at midlife.Conclusions: These results suggest that education, smoking, physical activity, diabetes, and stroke are all modifiable factors associated with cognitive decline. If these factors are determined to be causal, controlling them could minimize worldwide levels of cognitive decline. However, any global prevention strategy may need to consider ethno-regional differences. [ABSTRACT FROM AUTHOR]

Background: Pregnant women with metabolic risk factors are at high risk of complications. We aimed to assess whether a Mediterranean-style diet reduces adverse pregnancy outcomes in high-risk women.Methods and Findings: We conducted a multicentre randomised trial in 5 maternity units (4 in London and 1 in Birmingham) between 12 September 2014 and 29 February 2016. We randomised inner-city pregnant women with metabolic risk factors (obesity, chronic hypertension, or hypertriglyceridaemia) to a Mediterranean-style diet with high intake of nuts, extra virgin olive oil, fruits, vegetables, nonrefined grains, and legumes; moderate to high consumption of fish; low to moderate intake of poultry and dairy products; low intake of red and processed meat; and avoidance of sugary drinks, fast food, and food rich in animal fat versus usual care. Participants received individualised dietary advice at 18, 20, and 28 weeks' gestation. The primary endpoints were composite maternal (gestational diabetes or preeclampsia) and composite offspring (stillbirth, small for gestational age, or admission to neonatal care unit) outcomes prioritised by a Delphi survey. We used an intention-to-treat (ITT) analysis with multivariable models and identified the stratification variables and prognostic factors a priori. We screened 7,950 and randomised 1,252 women. Baseline data were available for 593 women in the intervention (93.3% follow-up, 553/593) and 612 in the control (95.6% follow-up, 585/612) groups. Over a quarter of randomised women were primigravida (330/1,205; 27%), 60% (729/1,205) were of Black or Asian ethnicity, and 69% (836/1,205) were obese. Women in the intervention arm consumed more nuts (70.1% versus 22.9%; adjusted odds ratio [aOR] 6.8, 95% confidence interval [CI] 4.3-10.6, p ≤ 0.001) and extra virgin olive oil (93.2% versus 49.0%; aOR 32.2, 95% CI 16.0-64.6, p ≤ 0.001) than controls; increased their intake of fish (p < 0.001), white meat (p < 0.001), and pulses (p = 0.05); and reduced their intake of red meat (p < 0.001), butter, margarine, and cream (p < 0.001). There was no significant reduction in the composite maternal (22.8% versus 28.6%; aOR 0.76, 95% CI 0.56-1.03, p = 0.08) or composite offspring (17.3% versus 20.9%; aOR 0.79, 95% CI 0.58-1.08, p = 0.14) outcomes. There was an apparent reduction in the odds of gestational diabetes by 35% (aOR 0.65, 95% CI 0.47-0.91, p = 0.01) but not in other individual components of the composite outcomes. Mothers gained less gestational weight (mean 6.8 versus 8.3 kg; adjusted difference -1.2 Kg, 95% CI -2.2 to -0.2, p = 0.03) with intervention versus control. There was no difference in any of the other maternal and offspring complications between both groups. When we pooled findings from the Effect of Simple, Targeted Diet in Pregnant Women With Metabolic Risk Factors on Pregnancy Outcomes (ESTEEM) trial with similar trials using random effects meta-analysis, we observed a significant reduction in gestational diabetes (odds ratio [OR] 0.67, 95% CI 0.53-0.84, I2 = 0%), with no heterogeneity (2 trials, 2,397 women). The study's limitations include the use of participant reported tools for adherence to the intervention instead of objective biomarkers.Conclusions: A simple, individualised, Mediterranean-style diet in pregnancy did not reduce the overall risk of adverse maternal and offspring complications but has the potential to reduce gestational weight gain and the risk of gestational diabetes.Trial Registration: ClinicalTrials.gov NCT02218931. [ABSTRACT FROM AUTHOR]

Background: Data are lacking from physical activity (PA) trials with long-term follow-up of both objectively measured PA levels and robust health outcomes. Two primary care 12-week pedometer-based walking interventions in adults and older adults (PACE-UP and PACE-Lift) found sustained objectively measured PA increases at 3 and 4 years, respectively. We aimed to evaluate trial intervention effects on long-term health outcomes relevant to walking interventions, using routine primary care data.Methods and Findings: Randomisation was from October 2012 to November 2013 for PACE-UP participants from seven general (family) practices and October 2011 to October 2012 for PACE-Lift participants from three practices. We downloaded primary care data, masked to intervention or control status, for 1,001 PACE-UP participants aged 45-75 years, 36% (361) male, and 296 PACE-Lift participants, aged 60-75 years, 46% (138) male, who gave written informed consent, for 4-year periods following randomisation. The following new events were counted for all participants, including those with preexisting diseases (apart from diabetes, for which existing cases were excluded): nonfatal cardiovascular, total cardiovascular (including fatal), incident diabetes, depression, fractures, and falls. Intervention effects on time to first event post-randomisation were modelled using Cox regression for all outcomes, except for falls, which used negative binomial regression to allow for multiple events, adjusting for age, sex, and study. Absolute risk reductions (ARRs) and numbers needed to treat (NNTs) were estimated. Data were downloaded for 1,297 (98%) of 1,321 trial participants. Event rates were low (<20 per group) for outcomes, apart from fractures and falls. Cox hazard ratios for time to first event post-randomisation for interventions versus controls were nonfatal cardiovascular 0.24 (95% confidence interval [CI] 0.07-0.77, p = 0.02), total cardiovascular 0.34 (95% CI 0.12-0.91, p = 0.03), diabetes 0.75 (95% CI 0.42-1.36, p = 0.34), depression 0.98 (95% CI 0.46-2.07, p = 0.96), and fractures 0.56 (95% CI 0.35-0.90, p = 0.02). Negative binomial incident rate ratio for falls was 1.07 (95% CI 0.78-1.46, p = 0.67). ARR and NNT for cardiovascular events were nonfatal 1.7% (95% CI 0.5%-2.1%), NNT = 59 (95% CI 48-194); total 1.6% (95% CI 0.2%-2.2%), NNT = 61 (95% CI 46-472); and for fractures 3.6% (95% CI 0.8%-5.4%), NNT = 28 (95% CI 19-125). Main limitations were that event rates were low and only events recorded in primary care records were counted; however, any underrecording would not have differed by intervention status and so should not have led to bias.Conclusions: Routine primary care data used to assess long-term trial outcomes demonstrated significantly fewer new cardiovascular events and fractures in intervention participants at 4 years. No statistically significant differences between intervention and control groups were demonstrated for other events. Short-term primary care pedometer-based walking interventions can produce long-term health benefits and should be more widely used to help address the public health inactivity challenge.Trial Registrations: PACE-UP isrctn.com ISRCTN98538934; PACE-Lift isrctn.com ISRCTN42122561. [ABSTRACT FROM AUTHOR]

Background: Economic incentives through health insurance may promote healthier behaviors. Little is known about health and economic impacts of incentivizing diet, a leading risk factor for diabetes and cardiovascular disease (CVD), through Medicare and Medicaid.Methods and Findings: A validated microsimulation model (CVD-PREDICT) estimated CVD and diabetes cases prevented, quality-adjusted life years (QALYs), health-related costs (formal healthcare, informal healthcare, and lost-productivity costs), and incremental cost-effectiveness ratios (ICERs) of two policy scenarios for adults within Medicare and Medicaid, compared to a base case of no new intervention: (1) 30% subsidy on fruits and vegetables ("F&V incentive") and (2) 30% subsidy on broader healthful foods including F&V, whole grains, nuts/seeds, seafood, and plant oils ("healthy food incentive"). Inputs included national demographic and dietary data from the National Health and Nutrition Examination Survey (NHANES) 2009-2014, policy effects and diet-disease effects from meta-analyses, and policy and health-related costs from established sources. Overall, 82 million adults (35-80 years old) were on Medicare and/or Medicaid. The mean (SD) age was 68.1 (11.4) years, 56.2% were female, and 25.5% were non-whites. Health and cost impacts were simulated over the lifetime of current Medicare and Medicaid participants (average simulated years = 18.3 years). The F&V incentive was estimated to prevent 1.93 million CVD events, gain 4.64 million QALYs, and save $39.7 billion in formal healthcare costs. For the healthy food incentive, corresponding gains were 3.28 million CVD and 0.12 million diabetes cases prevented, 8.40 million QALYs gained, and $100.2 billion in formal healthcare costs saved, respectively. From a healthcare perspective, both scenarios were cost-effective at 5 years and beyond, with lifetime ICERs of $18,184/QALY (F&V incentive) and $13,194/QALY (healthy food incentive). From a societal perspective including informal healthcare costs and lost productivity, respective ICERs were $14,576/QALY and $9,497/QALY. Results were robust in probabilistic sensitivity analyses and a range of one-way sensitivity and subgroup analyses, including by different durations of the intervention (5, 10, and 20 years and lifetime), food subsidy levels (20%, 50%), insurance groups (Medicare, Medicaid, and dual-eligible), and beneficiary characteristics within each insurance group (age, race/ethnicity, education, income, and Supplemental Nutrition Assistant Program [SNAP] status). Simulation studies such as this one provide quantitative estimates of benefits and uncertainty but cannot directly prove health and economic impacts.Conclusions: Economic incentives for healthier foods through Medicare and Medicaid could generate substantial health gains and be highly cost-effective. [ABSTRACT FROM AUTHOR]

Background: The prevalence of diabetes is increasing rapidly in low- and middle-income countries (LMICs), urgently requiring detailed evidence to guide the response of health systems to this epidemic. In an effort to understand at what step in the diabetes care continuum individuals are lost to care, and how this varies between countries and population groups, this study examined health system performance for diabetes among adults in 28 LMICs using a cascade of care approach.Methods and Findings: We pooled individual participant data from nationally representative surveys done between 2008 and 2016 in 28 LMICs. Diabetes was defined as fasting plasma glucose ≥ 7.0 mmol/l (126 mg/dl), random plasma glucose ≥ 11.1 mmol/l (200 mg/dl), HbA1c ≥ 6.5%, or reporting to be taking medication for diabetes. Stages of the care cascade were as follows: tested, diagnosed, lifestyle advice and/or medication given ("treated"), and controlled (HbA1c < 8.0% or equivalent). We stratified cascades of care by country, geographic region, World Bank income group, and individual-level characteristics (age, sex, educational attainment, household wealth quintile, and body mass index [BMI]). We then used logistic regression models with country-level fixed effects to evaluate predictors of (1) testing, (2) treatment, and (3) control. The final sample included 847,413 adults in 28 LMICs (8 low income, 9 lower-middle income, 11 upper-middle income). Survey sample size ranged from 824 in Guyana to 750,451 in India. The prevalence of diabetes was 8.8% (95% CI: 8.2%-9.5%), and the prevalence of undiagnosed diabetes was 4.8% (95% CI: 4.5%-5.2%). Health system performance for management of diabetes showed large losses to care at the stage of being tested, and low rates of diabetes control. Total unmet need for diabetes care (defined as the sum of those not tested, tested but undiagnosed, diagnosed but untreated, and treated but with diabetes not controlled) was 77.0% (95% CI: 74.9%-78.9%). Performance along the care cascade was significantly better in upper-middle income countries, but across all World Bank income groups, only half of participants with diabetes who were tested achieved diabetes control. Greater age, educational attainment, and BMI were associated with higher odds of being tested, being treated, and achieving control. The limitations of this study included the use of a single glucose measurement to assess diabetes, differences in the approach to wealth measurement across surveys, and variation in the date of the surveys.Conclusions: The study uncovered poor management of diabetes along the care cascade, indicating large unmet need for diabetes care across 28 LMICs. Performance across the care cascade varied by World Bank income group and individual-level characteristics, particularly age, educational attainment, and BMI. This policy-relevant analysis can inform country-specific interventions and offers a baseline by which future progress can be measured. [ABSTRACT FROM AUTHOR]

The article presents a meta-data analysis exploring the interrelationship between maternal body mass index, gestational weight gain, and the risk of being overweight or obese throughout childhood, using data taken from Europe, North America, and Australia.. Topics explored include US Institute of Medicine,, individual participant data, Maternal Obesity and Childhood Outcomes; odds ratio, population attributable risk fraction, standard deviation score, and World Health Organization

Background: Non-communicable diseases (NCDs) are leading causes of premature disability and death worldwide. However, the lifetime risk of developing any NCD is unknown, as are the effects of shared common risk factors on this risk.Methods and Findings: Between July 6, 1989, and January 1, 2012, we followed participants from the prospective Rotterdam Study aged 45 years and older who were free from NCDs at baseline for incident stroke, heart disease, diabetes, chronic respiratory disease, cancer, and neurodegenerative disease. We quantified occurrence/co-occurrence and remaining lifetime risk of any NCD in a competing risk framework. We additionally studied the lifetime risk of any NCD, age at onset, and overall life expectancy for strata of 3 shared risk factors at baseline: smoking, hypertension, and overweight. During 75,354 person-years of follow-up from a total of 9,061 participants (mean age 63.9 years, 60.1% women), 814 participants were diagnosed with stroke, 1,571 with heart disease, 625 with diabetes, 1,004 with chronic respiratory disease, 1,538 with cancer, and 1,065 with neurodegenerative disease. NCDs tended to co-occur substantially, with 1,563 participants (33.7% of those who developed any NCD) diagnosed with multiple diseases during follow-up. The lifetime risk of any NCD from the age of 45 years onwards was 94.0% (95% CI 92.9%-95.1%) for men and 92.8% (95% CI 91.8%-93.8%) for women. These risks remained high (>90.0%) even for those without the 3 risk factors of smoking, hypertension, and overweight. Absence of smoking, hypertension, and overweight was associated with a 9.0-year delay (95% CI 6.3-11.6) in the age at onset of any NCD. Furthermore, the overall life expectancy for participants without these risk factors was 6.0 years (95% CI 5.2-6.8) longer than for those with all 3 risk factors. Participants aged 45 years and older without the 3 risk factors of smoking, hypertension, and overweight at baseline spent 21.6% of their remaining lifetime with 1 or more NCDs, compared to 31.8% of their remaining life for participants with all of these risk factors at baseline. This difference corresponds to a 2-year compression of morbidity of NCDs. Limitations of this study include potential residual confounding, unmeasured changes in risk factor profiles during follow-up, and potentially limited generalisability to different healthcare settings and populations not of European descent.Conclusions: Our study suggests that in this western European community, 9 out of 10 individuals aged 45 years and older develop an NCD during their remaining lifetime. Among those individuals who develop an NCD, at least a third are subsequently diagnosed with multiple NCDs. Absence of 3 common shared risk factors is associated with compression of morbidity of NCDs. These findings underscore the importance of avoidance of these common shared risk factors to reduce the premature morbidity and mortality attributable to NCDs. [ABSTRACT FROM AUTHOR]

Background: There is little systematic assessment of how total health expenditure is distributed across diseases and comorbidities. The objective of this study was to use statistical methods to disaggregate all publicly funded health expenditure by disease and comorbidities in order to answer three research questions: (1) What is health expenditure by disease phase for noncommunicable diseases (NCDs) in New Zealand? (2) Is the cost of having two NCDs more or less than that expected given the independent costs of each NCD? (3) How is total health spending disaggregated by NCDs across age and by sex?Methods and Findings: We used linked data for all adult New Zealanders for publicly funded events, including hospitalisation, outpatient, pharmaceutical, laboratory testing, and primary care from 1 July 2007 to 30 June 2014. These data include 18.9 million person-years and $26.4 billion in spending (US$ 2016). We used case definition algorithms to identify if a person had any of six NCDs (cancer, cardiovascular disease [CVD], diabetes, musculoskeletal, neurological, and a chronic lung/liver/kidney [LLK] disease). Indicator variables were used to identify the presence of any of the 15 possible comorbidity pairings of these six NCDs. Regression was used to estimate excess annual health expenditure per person. Cause deletion methods were used to estimate total population expenditure by disease. A majority (59%) of health expenditure was attributable to NCDs. Expenditure due to diseases was generally highest in the year of diagnosis and year of death. A person having two diseases simultaneously generally had greater health expenditure than the expected sum of having the diseases separately, for all 15 comorbidity pairs except the CVD-cancer pair. For example, a 60-64-year-old female with none of the six NCDs had $633 per annum expenditure. If she had both CVD and chronic LLK, additional expenditure for CVD separately was $6,443/$839/$9,225 for the first year of diagnosis/prevalent years/last year of life if dying of CVD; additional expenditure for chronic LLK separately was $6,443/$1,291/$9,051; and the additional comorbidity expenditure of having both CVD and LLK was $2,456 (95% confidence interval [CI] $2,238-$2,674). The pattern was similar for males (e.g., additional comorbidity expenditure for a 60-64-year-old male with CVD and chronic LLK was $2,498 [95% CI $2,264-$2,632]). In addition to this, the excess comorbidity costs for a person with two diseases was greater at younger ages, e.g., excess expenditure for 45-49-year-old males with CVD and chronic LLK was 10 times higher than for 75-79-year-old males and six times higher for females. At the population level, 23.8% of total health expenditure was attributable to higher costs of having one of the 15 comorbidity pairs over and above the six NCDs separately; of the remaining expenditure, CVD accounted for 18.7%, followed by musculoskeletal (16.2%), neurological (14.4%), cancer (14.1%), chronic LLK disease (7.4%), and diabetes (5.5%). Major limitations included incomplete linkage to all costed events (although these were largely non-NCD events) and missing private expenditure.Conclusions: The costs of having two NCDs simultaneously is typically superadditive, and more so for younger adults. Neurological and musculoskeletal diseases contributed the largest health system costs, in accord with burden of disease studies finding that they contribute large morbidity. Just as burden of disease methodology has advanced the understanding of disease burden, there is a need to create disease-based costing studies that facilitate the disaggregation of health budgets at a national level. [ABSTRACT FROM AUTHOR]

Background: Obesity increases the risk for developing gestational diabetes mellitus (GDM) and preeclampsia (PE), which both associate with increased risk for type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD) in women in later life. In the general population, metabolic syndrome (MetS) associates with T2DM and CVD. The impact of maternal MetS on pregnancy outcomes, in nulliparous pregnant women, has not been investigated.Methods and Findings: Low-risk, nulliparous women were recruited to the multi-centre, international prospective Screening for Pregnancy Endpoints (SCOPE) cohort between 11 November 2004 and 28 February 2011. Women were assessed for a range of demographic, lifestyle, and metabolic health variables at 15 ± 1 weeks' gestation. MetS was defined according to International Diabetes Federation (IDF) criteria for adults: waist circumference ≥80 cm, along with any 2 of the following: raised trigycerides (≥1.70 mmol/l [≥150 mg/dl]), reduced high-density lipoprotein cholesterol (<1.29 mmol/l [<50 mg/dl]), raised blood pressure (BP) (i.e., systolic BP ≥130 mm Hg or diastolic BP ≥85 mm Hg), or raised plasma glucose (≥5.6 mmol/l). Log-binomial regression analyses were used to examine the risk for each pregnancy outcome (GDM, PE, large for gestational age [LGA], small for gestational age [SGA], and spontaneous preterm birth [sPTB]) with each of the 5 individual components for MetS and as a composite measure (i.e., MetS, as defined by the IDF). The relative risks, adjusted for maternal BMI, age, study centre, ethnicity, socioeconomic index, physical activity, smoking status, depression status, and fetal sex, are reported. A total of 5,530 women were included, and 12.3% (n = 684) had MetS. Women with MetS were at an increased risk for PE by a factor of 1.63 (95% CI 1.23 to 2.15) and for GDM by 3.71 (95% CI 2.42 to 5.67). In absolute terms, for PE, women with MetS had an adjusted excess risk of 2.52% (95% CI 1.51% to 4.11%) and, for GDM, had an adjusted excess risk of 8.66% (95% CI 5.38% to 13.94%). Diagnosis of MetS was not associated with increased risk for LGA, SGA, or sPTB. Increasing BMI in combination with MetS increased the estimated probability for GDM and decreased the probability of an uncomplicated pregnancy. Limitations of this study are that there are several different definitions for MetS in the adult population, and as there are none for pregnancy, we cannot be sure that the IDF criteria are the most appropriate definition for pregnancy. Furthermore, MetS was assessed in the first trimester and may not reflect pre-pregnancy metabolic health status.Conclusions: We did not compare the impact of individual metabolic components with that of MetS as a composite, and therefore cannot conclude that MetS is better at identifying women at risk. However, more than half of the women who had MetS in early pregnancy developed a pregnancy complication compared with just over a third of women who did not have MetS. Furthermore, while increasing BMI increases the probability of GDM, the addition of MetS exacerbates this probability. Further studies are required to determine if individual MetS components act synergistically or independently. [ABSTRACT FROM AUTHOR]

Background: The current acute kidney injury (AKI) risk prediction model for patients undergoing percutaneous coronary intervention (PCI) from the American College of Cardiology (ACC) National Cardiovascular Data Registry (NCDR) employed regression techniques. This study aimed to evaluate whether models using machine learning techniques could significantly improve AKI risk prediction after PCI.Methods and Findings: We used the same cohort and candidate variables used to develop the current NCDR CathPCI Registry AKI model, including 947,091 patients who underwent PCI procedures between June 1, 2009, and June 30, 2011. The mean age of these patients was 64.8 years, and 32.8% were women, with a total of 69,826 (7.4%) AKI events. We replicated the current AKI model as the baseline model and compared it with a series of new models. Temporal validation was performed using data from 970,869 patients undergoing PCIs between July 1, 2016, and March 31, 2017, with a mean age of 65.7 years; 31.9% were women, and 72,954 (7.5%) had AKI events. Each model was derived by implementing one of two strategies for preprocessing candidate variables (preselecting and transforming candidate variables or using all candidate variables in their original forms), one of three variable-selection methods (stepwise backward selection, lasso regularization, or permutation-based selection), and one of two methods to model the relationship between variables and outcome (logistic regression or gradient descent boosting). The cohort was divided into different training (70%) and test (30%) sets using 100 different random splits, and the performance of the models was evaluated internally in the test sets. The best model, according to the internal evaluation, was derived by using all available candidate variables in their original form, permutation-based variable selection, and gradient descent boosting. Compared with the baseline model that uses 11 variables, the best model used 13 variables and achieved a significantly better area under the receiver operating characteristic curve (AUC) of 0.752 (95% confidence interval [CI] 0.749-0.754) versus 0.711 (95% CI 0.708-0.714), a significantly better Brier score of 0.0617 (95% CI 0.0615-0.0618) versus 0.0636 (95% CI 0.0634-0.0638), and a better calibration slope of observed versus predicted rate of 1.008 (95% CI 0.988-1.028) versus 1.036 (95% CI 1.015-1.056). The best model also had a significantly wider predictive range (25.3% versus 21.6%, p < 0.001) and was more accurate in stratifying AKI risk for patients. Evaluated on a more contemporary CathPCI cohort (July 1, 2015-March 31, 2017), the best model consistently achieved significantly better performance than the baseline model in AUC (0.785 versus 0.753), Brier score (0.0610 versus 0.0627), calibration slope (1.003 versus 1.062), and predictive range (29.4% versus 26.2%). The current study does not address implementation for risk calculation at the point of care, and potential challenges include the availability and accessibility of the predictors.Conclusions: Machine learning techniques and data-driven approaches resulted in improved prediction of AKI risk after PCI. The results support the potential of these techniques for improving risk prediction models and identification of patients who may benefit from risk-mitigation strategies. [ABSTRACT FROM AUTHOR]

Background: Type 2 diabetes mellitus and cardiovascular disease and have become leading causes of morbidity and mortality among Palestinian refugees in the Middle East, many of whom live in long-term settlements and receive grain-based food aid. The objective of this study was to estimate changes in type 2 diabetes and cardiovascular disease morbidity and mortality attributable to a transition from traditional food aid to either (i) a debit card restricted to food purchases, (ii) cash, or (iii) an alternative food parcel with less grain and more fruits and vegetables, each valued at $30/person/month.Methods and Findings: An individual-level microsimulation was created to estimate relationships between food aid delivery method, food consumption, type 2 diabetes, and cardiovascular disease morbidity and mortality using demographic data from the United Nations (UN; 2017) on 5,340,443 registered Palestinian refugees in Syria, Jordan, Lebanon, Gaza, and the West Bank, food consumption data (2011-2017) from households receiving traditional food parcel delivery of food aid (n = 1,507 households) and electronic debit card delivery of food aid (n = 1,047 households), and health data from a random 10% sample of refugees receiving medical care through the UN (2012-2015; n = 516,386). Outcome metrics included incidence per 1,000 person-years of hypertension, type 2 diabetes, atherosclerotic cardiovascular disease events, microvascular events (end-stage renal disease, diabetic neuropathy, and proliferative diabetic retinopathy), and all-cause mortality. The model estimated changes in total calories, sodium and potassium intake, fatty acid intake, and overall dietary quality (Mediterranean Dietary Score [MDS]) as mediators to each outcome metric. We did not observe that a change from food parcel to electronic debit card delivery of food aid or to cash aid led to a meaningful change in consumption, biomarkers, or disease outcomes. By contrast, a shift to an alternative food parcel with less grain and more fruits and vegetables was estimated to produce a 0.08 per 1,000 person-years decrease in the incidence of hypertension (95% confidence interval [CI] 0.05-0.11), 0.18 per 1,000 person-years decrease in the incidence of type 2 diabetes (95% CI 0.14-0.22), 0.18 per 1,000 person-years decrease in the incidence of atherosclerotic cardiovascular disease events (95% CI 0.17-0.19), and 0.02 decrease per 1,000 person-years all-cause mortality (95% CI 0.01 decrease to 0.04 increase) among those receiving aid. The benefits of this shift, however, could be neutralized by a small (2%) increase in compensatory (out-of-pocket) increases in consumption of refined grains, fats and oils, or confectionaries. A larger alternative parcel requiring an increase in total food aid expenditure by 27% would be more likely to have a clinically meaningful improvement on type 2 diabetes and cardiovascular disease incidence.Conclusions: Contrary to the supposition in the literature, our findings do not robustly support the theory that transitioning from traditional food aid to either debit card or cash delivery alone would necessarily reduce chronic disease outcomes. Rather, an alternative food parcel would be more effective, even after matching current budget ceilings. But compensatory increases in consumption of less healthy foods may neutralize the improvements from an alternative food parcel unless total aid funding were increased substantially. Our analysis is limited by uncertainty in estimates of modeling long-term outcomes from shorter-term trials, focusing on diabetes and cardiovascular outcomes for which validated equations are available instead of all nutrition-associated health outcomes, and using data from food frequency questionnaires in the absence of 24-hour dietary recall data. [ABSTRACT FROM AUTHOR]

Background: Maternal pre-conception obesity is a strong risk factor for childhood overweight. However, prenatal mechanisms and their effects in susceptible gestational periods that contribute to this risk are not well understood. We aimed to assess the impact of late-pregnancy dysglycemia in obese pregnancies with negative testing for gestational diabetes mellitus (GDM) on long-term mother-child outcomes.Methods and Findings: The prospective cohort study Programming of Enhanced Adiposity Risk in Childhood-Early Screening (PEACHES) (n = 1,671) enrolled obese and normal weight mothers from August 2010 to December 2015 with trimester-specific data on glucose metabolism including GDM status at the end of the second trimester and maternal glycated hemoglobin (HbA1c) at delivery as a marker for late-pregnancy dysglycemia (HbA1c ≥ 5.7% [39 mmol/mol]). We assessed offspring short- and long-term outcomes up to 4 years, and maternal glucose metabolism 3.5 years postpartum. Multivariable linear and log-binomial regression with effects presented as mean increments (Δ) or relative risks (RRs) with 95% confidence intervals (CIs) were used to examine the association between late-pregnancy dysglycemia and outcomes. Linear mixed-effects models were used to study the longitudinal development of offspring body mass index (BMI) z-scores. The contribution of late-pregnancy dysglycemia to the association between maternal pre-conception obesity and offspring BMI was estimated using mediation analysis. In all, 898 mother-child pairs were included in this unplanned interim analysis. Among obese mothers with negative testing for GDM (n = 448), those with late-pregnancy dysglycemia (n = 135, 30.1%) had higher proportions of excessive total gestational weight gain (GWG), excessive third-trimester GWG, and offspring with large-for-gestational-age birth weight than those without. Besides higher birth weight (Δ 192 g, 95% CI 100-284) and cord-blood C-peptide concentration (Δ 0.10 ng/ml, 95% CI 0.02-0.17), offspring of these women had greater weight gain during early childhood (Δ BMI z-score per year 0.18, 95% CI 0.06-0.30, n = 262) and higher BMI z-score at 4 years (Δ 0.58, 95% CI 0.18-0.99, n = 43) than offspring of the obese, GDM-negative mothers with normal HbA1c values at delivery. Late-pregnancy dysglycemia in GDM-negative mothers accounted for about one-quarter of the association of maternal obesity with offspring BMI at age 4 years (n = 151). In contrast, childhood BMI z-scores were not affected by a diagnosis of GDM in obese pregnancies (GDM-positive: 0.58, 95% CI 0.36-0.79, versus GDM-negative: 0.62, 95% CI 0.44-0.79). One mechanism triggering late-pregnancy dysglycemia in obese, GDM-negative mothers was related to excessive third-trimester weight gain (RR 1.72, 95% CI 1.12-2.65). Furthermore, in the maternal population, we found a 4-fold (RR 4.01, 95% CI 1.97-8.17) increased risk of future prediabetes or diabetes if obese, GDM-negative women had a high versus normal HbA1c at delivery (absolute risk: 43.2% versus 10.5%). There is a potential for misclassification bias as the predominantly used GDM test procedure changed over the enrollment period. Further studies are required to validate the findings and elucidate the possible third-trimester factors contributing to future mother-child health status.Conclusions: Findings from this interim analysis suggest that offspring of obese mothers treated because of a diagnosis of GDM appeared to have a better BMI outcome in childhood than those of obese mothers who-following negative GDM testing-remained untreated in the last trimester and developed dysglycemia. Late-pregnancy dysglycemia related to uncontrolled weight gain may contribute to the development of child overweight and maternal diabetes. Our data suggest that negative GDM testing in obese pregnancies is not an "all-clear signal" and should not lead to reduced attention and risk awareness of physicians and obese women. Effective strategies are needed to maintain third-trimester glycemic and weight gain control among otherwise healthy obese pregnant women. [ABSTRACT FROM AUTHOR]

Background: We aimed to investigate prospective associations of circulating or adipose tissue odd-chain fatty acids 15:0 and 17:0 and trans-palmitoleic acid, t16:1n-7, as potential biomarkers of dairy fat intake, with incident type 2 diabetes (T2D).Methods and Findings: Sixteen prospective cohorts from 12 countries (7 from the United States, 7 from Europe, 1 from Australia, 1 from Taiwan) performed new harmonised individual-level analysis for the prospective associations according to a standardised plan. In total, 63,682 participants with a broad range of baseline ages and BMIs and 15,180 incident cases of T2D over the average of 9 years of follow-up were evaluated. Study-specific results were pooled using inverse-variance-weighted meta-analysis. Prespecified interactions by age, sex, BMI, and race/ethnicity were explored in each cohort and were meta-analysed. Potential heterogeneity by cohort-specific characteristics (regions, lipid compartments used for fatty acid assays) was assessed with metaregression. After adjustment for potential confounders, including measures of adiposity (BMI, waist circumference) and lipogenesis (levels of palmitate, triglycerides), higher levels of 15:0, 17:0, and t16:1n-7 were associated with lower incidence of T2D. In the most adjusted model, the hazard ratio (95% CI) for incident T2D per cohort-specific 10th to 90th percentile range of 15:0 was 0.80 (0.73-0.87); of 17:0, 0.65 (0.59-0.72); of t16:1n7, 0.82 (0.70-0.96); and of their sum, 0.71 (0.63-0.79). In exploratory analyses, similar associations for 15:0, 17:0, and the sum of all three fatty acids were present in both genders but stronger in women than in men (pinteraction < 0.001). Whereas studying associations with biomarkers has several advantages, as limitations, the biomarkers do not distinguish between different food sources of dairy fat (e.g., cheese, yogurt, milk), and residual confounding by unmeasured or imprecisely measured confounders may exist.Conclusions: In a large meta-analysis that pooled the findings from 16 prospective cohort studies, higher levels of 15:0, 17:0, and t16:1n-7 were associated with a lower risk of T2D. [ABSTRACT FROM AUTHOR]

Background: The Supplemental Nutrition Assistance Program (SNAP) provides approximately US$70 billion annually to support food purchases by low-income households, supporting approximately 1 in 7 Americans. In the 2018 Farm Bill, potential SNAP revisions to improve diets and health could include financial incentives, disincentives, or restrictions for certain foods. However, the overall and comparative impacts on health outcomes and costs are not established. We aimed to estimate the health impact, program and healthcare costs, and cost-effectiveness of food incentives, disincentives, or restrictions in SNAP.Methods and Findings: We used a validated microsimulation model (CVD-PREDICT), populated with national data on adult SNAP participants from the National Health and Nutrition Examination Survey (NHANES) 2009-2014, policy effects from SNAP pilots and food pricing meta-analyses, diet-disease effects from meta-analyses, and policy, food, and healthcare costs from published literature to estimate the overall and comparative impacts of 3 dietary policy interventions: (1) a 30% incentive for fruits and vegetables (F&V), (2) a 30% F&V incentive with a restriction of sugar-sweetened beverages (SSBs), and (3) a broader incentive/disincentive program for multiple foods that also preserves choice (SNAP-plus), combining 30% incentives for F&V, nuts, whole grains, fish, and plant-based oils and 30% disincentives for SSBs, junk food, and processed meats. Among approximately 14.5 million adults on SNAP at baseline with mean age 52 years, our simulation estimates that the F&V incentive over 5 years would prevent 38,782 cardiovascular disease (CVD) events, gain 18,928 quality-adjusted life years (QALYs), and save $1.21 billion in healthcare costs. Adding SSB restriction increased gains to 93,933 CVD events prevented, 45,864 QALYs gained, and $4.33 billion saved. For SNAP-plus, corresponding gains were 116,875 CVD events prevented, 56,056 QALYs gained, and $5.28 billion saved. Over a lifetime, the F&V incentive would prevent approximately 303,900 CVD events, gain 649,000 QALYs, and save $6.77 billion in healthcare costs. Adding SSB restriction increased gains to approximately 797,900 CVD events prevented, 2.11 million QALYs gained, and $39.16 billion in healthcare costs saved. For SNAP-plus, corresponding gains were approximately 940,000 CVD events prevented, 2.47 million QALYs gained, and $41.93 billion saved. From a societal perspective (including programmatic costs but excluding food subsidy costs as an intra-societal transfer), all 3 scenarios were cost-saving. From a government affordability perspective (i.e., incorporating food subsidy costs, including for children and young adults for whom no health gains were modeled), the F&V incentive was of low cost-effectiveness at 5 years (incremental cost-effectiveness ratio: $548,053/QALY) but achieved cost-effectiveness ($66,525/QALY) over a lifetime. Adding SSB restriction, the intervention was cost-effective at 10 years ($68,857/QALY) and very cost-effective at 20 years ($26,435/QALY) and over a lifetime ($5,216/QALY). The combined incentive/disincentive program produced the largest health gains and reduced both healthcare and food costs, with net cost-savings of $10.16 billion at 5 years and $63.33 billion over a lifetime. Results were consistent in probabilistic sensitivity analyses: for example, from a societal perspective, 1,000 of 1,000 iterations (100%) were cost-saving for all 3 interventions. Due to the nature of simulation studies, the findings cannot prove the health and cost impacts of national SNAP interventions.Conclusions: Leveraging healthier eating through SNAP could generate substantial health benefits and be cost-effective or cost-saving. A combined food incentive/disincentive program appears most effective and may be most attractive to policy-makers. [ABSTRACT FROM AUTHOR]

Background: Type 2 diabetes (T2D) is a heterogeneous disease for which (1) disease-causing pathways are incompletely understood and (2) subclassification may improve patient management. Unlike other biomarkers, germline genetic markers do not change with disease progression or treatment. In this paper, we test whether a germline genetic approach informed by physiology can be used to deconstruct T2D heterogeneity. First, we aimed to categorize genetic loci into groups representing likely disease mechanistic pathways. Second, we asked whether the novel clusters of genetic loci we identified have any broad clinical consequence, as assessed in four separate subsets of individuals with T2D.Methods and Findings: In an effort to identify mechanistic pathways driven by established T2D genetic loci, we applied Bayesian nonnegative matrix factorization (bNMF) clustering to genome-wide association study (GWAS) results for 94 independent T2D genetic variants and 47 diabetes-related traits. We identified five robust clusters of T2D loci and traits, each with distinct tissue-specific enhancer enrichment based on analysis of epigenomic data from 28 cell types. Two clusters contained variant-trait associations indicative of reduced beta cell function, differing from each other by high versus low proinsulin levels. The three other clusters displayed features of insulin resistance: obesity mediated (high body mass index [BMI] and waist circumference [WC]), "lipodystrophy-like" fat distribution (low BMI, adiponectin, and high-density lipoprotein [HDL] cholesterol, and high triglycerides), and disrupted liver lipid metabolism (low triglycerides). Increased cluster genetic risk scores were associated with distinct clinical outcomes, including increased blood pressure, coronary artery disease (CAD), and stroke. We evaluated the potential for clinical impact of these clusters in four studies containing individuals with T2D (Metabolic Syndrome in Men Study [METSIM], N = 487; Ashkenazi, N = 509; Partners Biobank, N = 2,065; UK Biobank [UKBB], N = 14,813). Individuals with T2D in the top genetic risk score decile for each cluster reproducibly exhibited the predicted cluster-associated phenotypes, with approximately 30% of all individuals assigned to just one cluster top decile. Limitations of this study include that the genetic variants used in the cluster analysis were restricted to those associated with T2D in populations of European ancestry.Conclusion: Our approach identifies salient T2D genetically anchored and physiologically informed pathways, and supports the use of genetics to deconstruct T2D heterogeneity. Classification of patients by these genetic pathways may offer a step toward genetically informed T2D patient management. [ABSTRACT FROM AUTHOR]

Background: Observations from statin clinical trials and from Mendelian randomization studies suggest that low low-density lipoprotein cholesterol (LDL-C) concentrations may be associated with increased risk of type 2 diabetes mellitus (T2DM). Despite the findings from statin clinical trials and genetic studies, there is little direct evidence implicating low LDL-C concentrations in increased risk of T2DM.Methods and Findings: We used de-identified electronic health records (EHRs) at Vanderbilt University Medical Center to compare the risk of T2DM in a cross-sectional study among individuals with very low (≤60 mg/dl, N = 8,943) and normal (90-130 mg/dl, N = 71,343) LDL-C levels calculated using the Friedewald formula. LDL-C levels associated with statin use, hospitalization, or a serum albumin level < 3 g/dl were excluded. We used a 2-phase approach: in 1/3 of the sample (discovery) we used T2DM phenome-wide association study codes (phecodes) to identify cases and controls, and in the remaining 2/3 (validation) we identified T2DM cases and controls using a validated algorithm. The analysis plan for the validation phase was constructed at the time of the design of that component of the study. The prevalence of T2DM in the very low and normal LDL-C groups was compared using logistic regression with adjustment for age, race, sex, body mass index (BMI), high-density lipoprotein cholesterol, triglycerides, and duration of care. Secondary analyses included prespecified stratification by sex, race, BMI, and LDL-C level. In the discovery cohort, phecodes related to T2DM were significantly more frequent in the very low LDL-C group. In the validation cohort (N = 33,039 after applying the T2DM algorithm to identify cases and controls), the risk of T2DM was increased in the very low compared to normal LDL-C group (odds ratio [OR] 2.06, 95% CI 1.80-2.37; P < 2 × 10-16). The findings remained significant in sensitivity analyses. The association between low LDL-C levels and T2DM was significant in males (OR 2.43, 95% CI 2.00-2.95; P < 2 × 10-16) and females (OR 1.74, 95% CI 1.42-2.12; P = 6.88 × 10-8); in normal weight (OR 2.18, 95% CI 1.59-2.98; P = 1.1× 10-6), overweight (OR 2.17, 95% CI 1.65-2.83; P = 1.73× 10-8), and obese (OR 2.00, 95% CI 1.65-2.41; P = 8 × 10-13) categories; and in individuals with LDL-C < 40 mg/dl (OR 2.31, 95% CI 1.71-3.10; P = 3.01× 10-8) and LDL-C 40-60 mg/dl (OR 1.99, 95% CI 1.71-2.32; P < 2.0× 10-16). The association was significant in individuals of European ancestry (OR 2.67, 95% CI 2.25-3.17; P < 2 × 10-16) but not in those of African ancestry (OR 1.09, 95% CI 0.81-1.46; P = 0.56). A limitation was that we only compared groups with very low and normal LDL-C levels; also, since this was not an inception cohort, we cannot exclude the possibility of reverse causation.Conclusions: Very low LDL-C concentrations occurring in the absence of statin treatment were significantly associated with T2DM risk in a large EHR population; this increased risk was present in both sexes and all BMI categories, and in individuals of European ancestry but not of African ancestry. Longitudinal cohort studies to assess the relationship between very low LDL-C levels not associated with lipid-lowering therapy and risk of developing T2DM will be important. [ABSTRACT FROM AUTHOR]

Background: Little prospective evidence exists about risk factors and prognosis of acute pancreatitis in China. We examined the associations of certain metabolic and lifestyle factors with risk of acute pancreatitis in Chinese adults.Methods and Findings: The prospective China Kadoorie Biobank (CKB) recruited 512,891 adults aged 30 to 79 years from 5 urban and 5 rural areas between 25 June 2004 and 15 July 2008. During 9.2 years of follow-up (to 1 January 2015), 1,079 cases of acute pancreatitis were recorded. Cox regression was used to estimate adjusted hazard ratios (HRs) for acute pancreatitis associated with various metabolic and lifestyle factors among all or male (for smoking and alcohol drinking) participants. Overall, the mean waist circumference (WC) was 82.1 cm (SD 9.8) cm in men and 79.0 cm (SD 9.5) cm in women, 6% had diabetes, and 6% had gallbladder disease at baseline. WC was positively associated with risk of acute pancreatitis, with an adjusted HR of 1.35 (95% CI 1.27-1.43; p < 0.001) per 1-SD-higher WC. Individuals with diabetes or gallbladder disease had HRs of 1.34 (1.07-1.69; p = 0.01) and 2.42 (2.03-2.88; p < 0.001), respectively. Physical activity was inversely associated with risk of acute pancreatitis, with each 4 metabolic equivalent of task (MET) hours per day (MET-h/day) higher physical activity associated with an adjusted HR of 0.95 (0.91-0.99; p = 0.03). Compared with those without any metabolic risk factors (i.e., obesity, diabetes, gallbladder disease, and physical inactivity), the HRs of acute pancreatitis for those with 1, 2, or ≥3 risk factors were 1.61 (1.47-1.76), 2.36 (2.01-2.78), and 3.41 (2.46-4.72), respectively (p < 0.001). Among men, heavy alcohol drinkers (≥420 g/week) had an HR of 1.52 (1.11-2.09; p = 0.04, compared with abstainers), and current regular smokers had an HR of 1.45 (1.28-1.64; p = 0.02, compared with never smokers). Following a diagnosis of acute pancreatitis, there were higher risks of pancreatic cancer (HR = 8.26 [3.42-19.98]; p < 0.001; 13 pancreatic cancer cases) and death (1.53 [1.17-2.01]; p = 0.002; 89 deaths). Other diseases of the pancreas had similar risk factor profiles and prognosis to acute pancreatitis. The main study limitations are ascertainment of pancreatitis using hospital records and residual confounding.Conclusions: In this relatively lean Chinese population, several modifiable metabolic and lifestyle factors were associated with higher risks of acute pancreatitis, and individuals with acute pancreatitis had higher risks of pancreatic cancer and death. [ABSTRACT FROM AUTHOR]

Background: Acute myocardial infarction (AMI) is the leading cause of death among people with diabetes mellitus (DM) and has been found to occur more frequently with extreme temperatures. With the increasing prevalence of DM and the rising global mean temperature, the number of heat-related AMI cases among DM patients may increase. This study compares excess risk of AMI during periods of extreme temperatures between patients with DM and without DM.Methods: Distributed lag nonlinear models (DLNMs) were used to estimate the short-term association between daily mean temperature and AMI admissions (International Classification of Diseases 9th revision [ICD-9] code: 410.00-410.99), stratified by DM status (ICD-9: 250.00-250.99), to all public hospitals in Hong Kong from 2002 to 2011, adjusting for other meteorological variables and air pollutants. Analyses were also stratified by season, age group, gender, and admission type (first admissions and readmissions). The admissions data and meteorological data were obtained from the Hong Kong Hospital Authority (HA) and the Hong Kong Observatory (HKO).Findings: A total of 53,769 AMI admissions were included in the study. AMI admissions among DM patients were linearly and negatively associated with temperature in the cold season (cumulative relative risk [cumRR] [95% confidence interval] in lag 0-22 days (12 °C versus 24 °C) = 2.10 [1.62-2.72]), while those among patients without DM only started increasing when temperatures dropped below 22 °C with a weaker association (cumRR = 1.43 [1.21-1.69]). In the hot season, AMI hospitalizations among DM patients started increasing when the temperature dropped below or rose above 28.8 °C (cumRR in lag 0-4 days [30.4 versus 28.8 °C] = 1.14 [1.00-1.31]), while those among patients without DM showed no association with temperature. The differences in sensitivity to temperature between patients with DM and without DM were most apparent in the group <75 years old and among first-admission cases in the cold season. The main limitation of this study was the unavailability of data on individual exposure to ambient temperature.Conclusions: DM patients had a higher increased risk of AMI admissions than non-DM patients during extreme temperatures. AMI admissions risks among DM patients rise sharply in both high and low temperatures, with a stronger effect in low temperatures, while AMI risk among non-DM patients only increased mildly in low temperatures. Targeted health protection guidelines should be provided to warn DM patients and physicians about the dangers of extreme temperatures. Further studies to project the impacts of AMI risks on DM patients by climate change are warranted. [ABSTRACT FROM AUTHOR]

Background: Cardiovascular disease (CVD) is the leading cause of mortality in India. Yet, evidence on the CVD risk of India's population is limited. To inform health system planning and effective targeting of interventions, this study aimed to determine how CVD risk-and the factors that determine risk-varies among states in India, by rural-urban location, and by individual-level sociodemographic characteristics.Methods and Findings: We used 2 large household surveys carried out between 2012 and 2014, which included a sample of 797,540 adults aged 30 to 74 years across India. The main outcome variable was the predicted 10-year risk of a CVD event as calculated with the Framingham risk score. The Harvard-NHANES, Globorisk, and WHO-ISH scores were used in secondary analyses. CVD risk and the prevalence of CVD risk factors were examined by state, rural-urban residence, age, sex, household wealth, and education. Mean CVD risk varied from 13.2% (95% CI: 12.7%-13.6%) in Jharkhand to 19.5% (95% CI: 19.1%-19.9%) in Kerala. CVD risk tended to be highest in North, Northeast, and South India. District-level wealth quintile (based on median household wealth in a district) and urbanization were both positively associated with CVD risk. Similarly, household wealth quintile and living in an urban area were positively associated with CVD risk among both sexes, but the associations were stronger among women than men. Smoking was more prevalent in poorer household wealth quintiles and in rural areas, whereas body mass index, high blood glucose, and systolic blood pressure were positively associated with household wealth and urban location. Men had a substantially higher (age-standardized) smoking prevalence (26.2% [95% CI: 25.7%-26.7%] versus 1.8% [95% CI: 1.7%-1.9%]) and mean systolic blood pressure (126.9 mm Hg [95% CI: 126.7-127.1] versus 124.3 mm Hg [95% CI: 124.1-124.5]) than women. Important limitations of this analysis are the high proportion of missing values (27.1%) in the main outcome variable, assessment of diabetes through a 1-time capillary blood glucose measurement, and the inability to exclude participants with a current or previous CVD event.Conclusions: This study identified substantial variation in CVD risk among states and sociodemographic groups in India-findings that can facilitate effective targeting of CVD programs to those most at risk and most in need. While the CVD risk scores used have not been validated in South Asian populations, the patterns of variation in CVD risk among the Indian population were similar across all 4 risk scoring systems. [ABSTRACT FROM AUTHOR]

Background: The major efficacy trials on diabetes prevention have used resource-intensive approaches to identify high-risk individuals and deliver lifestyle interventions. Such strategies are not feasible for wider implementation in low- and middle-income countries (LMICs). We aimed to evaluate the effectiveness of a peer-support lifestyle intervention in preventing type 2 diabetes among high-risk individuals identified on the basis of a simple diabetes risk score.Methods and Findings: The Kerala Diabetes Prevention Program was a cluster-randomized controlled trial conducted in 60 polling areas (clusters) of Neyyattinkara taluk (subdistrict) in Trivandrum district, Kerala state, India. Participants (age 30-60 years) were those with an Indian Diabetes Risk Score (IDRS) ≥60 and were free of diabetes on an oral glucose tolerance test (OGTT). A total of 1,007 participants (47.2% female) were enrolled (507 in the control group and 500 in the intervention group). Participants from intervention clusters participated in a 12-month community-based peer-support program comprising 15 group sessions (12 of which were led by trained lay peer leaders) and a range of community activities to support lifestyle change. Participants from control clusters received an education booklet with lifestyle change advice. The primary outcome was the incidence of diabetes at 24 months, diagnosed by an annual OGTT. Secondary outcomes were behavioral, clinical, and biochemical characteristics and health-related quality of life (HRQoL). A total of 964 (95.7%) participants were followed up at 24 months. Baseline characteristics of clusters and participants were similar between the study groups. After a median follow-up of 24 months, diabetes developed in 17.1% (79/463) of control participants and 14.9% (68/456) of intervention participants (relative risk [RR] 0.88, 95% CI 0.66-1.16, p = 0.36). At 24 months, compared with the control group, intervention participants had a greater reduction in IDRS score (mean difference: -1.50 points, p = 0.022) and alcohol use (RR 0.77, p = 0.018) and a greater increase in fruit and vegetable intake (≥5 servings/day) (RR 1.83, p = 0.008) and physical functioning score of the HRQoL scale (mean difference: 3.9 score, p = 0.016). The cost of delivering the peer-support intervention was US$22.5 per participant. There were no adverse events related to the intervention. We did not adjust for multiple comparisons, which may have increased the overall type I error rate.Conclusions: A low-cost community-based peer-support lifestyle intervention resulted in a nonsignificant reduction in diabetes incidence in this high-risk population at 24 months. However, there were significant improvements in some cardiovascular risk factors and physical functioning score of the HRQoL scale.Trial Registration: Australia and New Zealand Clinical Trials Registry ACTRN12611000262909. [ABSTRACT FROM AUTHOR]

Background: Aiming to contribute to prevention of cardiovascular disease (CVD), the National Health Service (NHS) Health Check programme has been implemented across England since 2009. The programme involves cardiovascular risk stratification-at 5-year intervals-of all adults between the ages of 40 and 74 years, excluding any with preexisting vascular conditions (including CVD, diabetes mellitus, and hypertension, among others), and offers treatment to those at high risk. However, the cost-effectiveness and equity of population CVD screening is contested. This study aimed to determine whether the NHS Health Check programme is cost-effective and equitable in a city with high levels of deprivation and CVD.Methods and Findings: IMPACTNCD is a dynamic stochastic microsimulation policy model, calibrated to Liverpool demographics, risk factor exposure, and CVD epidemiology. Using local and national data, as well as drawing on health and social care disease costs and health-state utilities, we modelled 5 scenarios from 2017 to 2040: Scenario (A): continuing current implementation of NHS Health Check;Scenario (B): implementation 'targeted' toward areas in the most deprived quintile with increased coverage and uptake;Scenario (C): 'optimal' implementation assuming optimal coverage, uptake, treatment, and lifestyle change;Scenario (D): scenario A combined with structural population-wide interventions targeting unhealthy diet and smoking;Scenario (E): scenario B combined with the structural interventions as above. We compared all scenarios with a counterfactual of no-NHS Health Check. Compared with no-NHS Health Check, the model estimated cumulative incremental cost-effectiveness ratio (ICER) (discounted £/quality-adjusted life year [QALY]) to be 11,000 (95% uncertainty interval [UI] -270,000 to 320,000) for scenario A, 1,500 (-91,000 to 100,000) for scenario B, -2,400 (-6,500 to 5,700) for scenario C, -5,100 (-7,400 to -3,200) for scenario D, and -5,000 (-7,400 to -3,100) for scenario E. Overall, scenario A is unlikely to become cost-effective or equitable, and scenario B is likely to become cost-effective by 2040 and equitable by 2039. Scenario C is likely to become cost-effective by 2030 and cost-saving by 2040. Scenarios D and E are likely to be cost-saving by 2021 and 2023, respectively, and equitable by 2025. The main limitation of the analysis is that we explicitly modelled CVD and diabetes mellitus only.Conclusions: According to our analysis of the situation in Liverpool, current NHS Health Check implementation appears neither equitable nor cost-effective. Optimal implementation is likely to be cost-saving but not equitable, while targeted implementation is likely to be both. Adding structural policies targeting cardiovascular risk factors could substantially improve equity and generate cost savings. [ABSTRACT FROM AUTHOR]

Background: Multimorbidity is increasingly common and is associated with adverse health outcomes, highlighting the need to broaden the single-disease framework that dominates medical research. We examined the role of midlife clinical characteristics, socioeconomic position, and behavioural factors in the development of cardiometabolic multimorbidity (at least 2 of diabetes, coronary heart disease, and stroke), along with how these factors modify risk of mortality.Methods and Findings: Data on 8,270 men and women were drawn from the Whitehall II cohort study, with mean follow-up of 23.7 years (1985 to 2017). Three sets of risk factors were assessed at age 50 years, each on a 5-point scale: clinical profile (hypertension, hypercholesterolemia, overweight/obesity, family history of cardiometabolic disease), occupational position, and behavioural factors (smoking, alcohol consumption, diet, physical activity). The outcomes examined were cardiometabolic disease (diabetes, coronary heart disease, stroke), cardiometabolic multimorbidity, and mortality. We used multi-state models to examine the role of risk factors in 5 components of the cardiometabolic disease trajectory: from healthy state to first cardiometabolic disease, from first cardiometabolic disease to cardiometabolic multimorbidity, from healthy state to death, from first cardiometabolic disease to death, and from cardiometabolic multimorbidity to death. A total of 2,501 participants developed 1 of the 3 cardiometabolic diseases, 511 developed cardiometabolic multimorbidity, and 1,406 died. When behavioural and clinical risk factors were considered individually, only smoking was associated with all five transitions. In a model containing all 3 risk factor scales, midlife clinical profile was the strongest predictor of first cardiometabolic disease (hazard ratio for the least versus most favourable profile: 3.74; 95% CI: 3.14-4.45) among disease-free participants. Among participants with 1 cardiometabolic disease, adverse midlife socioeconomic (1.54; 95% CI: 1.10-2.15) and behavioural factors (2.00; 95% CI: 1.40-2.85), but not clinical characteristics, were associated with progression to cardiometabolic multimorbidity. Only midlife behavioural factors predicted mortality among participants with cardiometabolic disease (2.12; 95% CI: 1.41-3.18) or cardiometabolic multimorbidity (3.47; 95% CI: 1.81-6.66). A limitation is that the study was not large enough to estimate transitions between each disease and subsequent outcomes and between all possible pairs of diseases.Conclusions: The importance of specific midlife factors in disease progression, from disease-free state to single disease, multimorbidity, and death, varies depending on the disease stage. While clinical risk factors at age 50 determine the risk of incident cardiometabolic disease in a disease-free population, midlife socioeconomic and behavioural factors are stronger predictors of progression to multimorbidity and mortality in people with cardiometabolic disease. [ABSTRACT FROM AUTHOR]

Background: Observational studies have reported that higher plasma 25-hydroxyvitamin D (25[OH]D) concentrations are associated with lower risks of diabetes, but it is unclear if these associations are causal. The aim of this study was to test the relevance of 25(OH)D for type 2 diabetes using genetically instrumented differences in plasma 25(OH)D concentrations.Methods and Findings: Data were available on four 25(OH)D single nucleotide polymorphisms (SNPs; n = 82,464), plasma 25(OH)D concentrations (n = 13,565), and cases with diabetes (n = 5,565) in the China Kadoorie Biobank (CKB). The effects on risk of diabetes were assessed by a genetic score using two 25(OH)D synthesis SNPs (DHCR7-rs12785878 and CYP2R1-rs10741657), with and without the addition of SNPs affecting the transport (GC/DBP-rs2282679) and catabolism (CYP24A1-rs6013897) of 25(OH)D. The CKB results were combined in a meta-analysis of 10 studies for the 2 synthesis SNPs (n = 58,312 cases) and 7 studies for all 4 SNPs (n = 32,796 cases). Mean (SD) 25(OH)D concentration was 62 (20) nmol/l in CKB, and the per allele effects of genetic scores on 25(OH)D were 2.87 (SE 0.39) for the synthesis SNPs and 3.54 (SE 0.32) for all SNPs. A 25-nmol/l higher biochemically measured 25(OH)D was associated with a 9% (95% CI: 0%-18%) lower risk of diabetes in CKB. In a meta-analysis of all studies, a 25-nmol/l higher genetically instrumented 25(OH)D concentration was associated with a 14% (95% CI: 3%-23%) lower risk of diabetes (p = 0.01) using the 2 synthesis SNPs. An equivalent difference in 25(OH)D using a genetic score with 4 SNPs was not significantly associated with diabetes (odds ratio 8%, 95% CI: -1% to 16%, lower risk, p = 0.07), but had some evidence of pleiotropy. A limitation of the meta-analysis was the access only to study level rather than individual level data.Conclusions: The concordant risks of diabetes for biochemically measured and genetically instrumented differences in 25(OH)D using synthesis SNPs provide evidence for a causal effect of higher 25(OH)D for prevention of diabetes. [ABSTRACT FROM AUTHOR]

Background: Around 0.3% of newborns will develop autoimmunity to pancreatic beta cells in childhood and subsequently develop type 1 diabetes before adulthood. Primary prevention of type 1 diabetes will require early intervention in genetically at-risk infants. The objective of this study was to determine to what extent genetic scores (two previous genetic scores and a merged genetic score) can improve the prediction of type 1 diabetes.Methods and Findings: The Environmental Determinants of Diabetes in the Young (TEDDY) study followed genetically at-risk children at 3- to 6-monthly intervals from birth for the development of islet autoantibodies and type 1 diabetes. Infants were enrolled between 1 September 2004 and 28 February 2010 and monitored until 31 May 2016. The risk (positive predictive value) for developing multiple islet autoantibodies (pre-symptomatic type 1 diabetes) and type 1 diabetes was determined in 4,543 children who had no first-degree relatives with type 1 diabetes and either a heterozygous HLA DR3 and DR4-DQ8 risk genotype or a homozygous DR4-DQ8 genotype, and in 3,498 of these children in whom genetic scores were calculated from 41 single nucleotide polymorphisms. In the children with the HLA risk genotypes, risk for developing multiple islet autoantibodies was 5.8% (95% CI 5.0%-6.6%) by age 6 years, and risk for diabetes by age 10 years was 3.7% (95% CI 3.0%-4.4%). Risk for developing multiple islet autoantibodies was 11.0% (95% CI 8.7%-13.3%) in children with a merged genetic score of >14.4 (upper quartile; n = 907) compared to 4.1% (95% CI 3.3%-4.9%, P < 0.001) in children with a genetic score of ≤14.4 (n = 2,591). Risk for developing diabetes by age 10 years was 7.6% (95% CI 5.3%-9.9%) in children with a merged score of >14.4 compared with 2.7% (95% CI 1.9%-3.6%) in children with a score of ≤14.4 (P < 0.001). Of 173 children with multiple islet autoantibodies by age 6 years and 107 children with diabetes by age 10 years, 82 (sensitivity, 47.4%; 95% CI 40.1%-54.8%) and 52 (sensitivity, 48.6%, 95% CI 39.3%-60.0%), respectively, had a score >14.4. Scores were higher in European versus US children (P = 0.003). In children with a merged score of >14.4, risk for multiple islet autoantibodies was similar and consistently >10% in Europe and in the US; risk was greater in males than in females (P = 0.01). Limitations of the study include that the genetic scores were originally developed from case-control studies of clinical diabetes in individuals of mainly European decent. It is, therefore, possible that it may not be suitable to all populations.Conclusions: A type 1 diabetes genetic score identified infants without family history of type 1 diabetes who had a greater than 10% risk for pre-symptomatic type 1 diabetes, and a nearly 2-fold higher risk than children identified by high-risk HLA genotypes alone. This finding extends the possibilities for enrolling children into type 1 diabetes primary prevention trials. [ABSTRACT FROM AUTHOR]

Background: Androgen excess is a defining feature of polycystic ovary syndrome (PCOS), which affects 10% of women and represents a lifelong metabolic disorder, with increased risk of type 2 diabetes, hypertension, and cardiovascular events. Previous studies have suggested an increased risk of nonalcoholic fatty liver disease (NAFLD) in individuals with PCOS and implicated androgen excess as a potential driver.Methods and Findings: We carried out a retrospective longitudinal cohort study utilizing a large primary care database in the United Kingdom, evaluating NAFLD rates in 63,120 women with PCOS and 121,064 age-, body mass index (BMI)-, and location-matched control women registered from January 2000 to May 2016. In 2 independent cohorts, we also determined the rate of NAFLD in women with a measurement of serum testosterone (n = 71,061) and sex hormone-binding globulin (SHBG; n = 49,625). We used multivariate Cox models to estimate the hazard ratio (HR) for NAFLD and found that women with PCOS had an increased rate of NAFLD (HR = 2.23, 95% CI 1.86-2.66, p < 0.001), also after adjusting for BMI or dysglycemia. Serum testosterone >3.0 nmol/L was associated with an increase in NAFLD (HR = 2.30, 95% CI 1.16-4.53, p = 0.017 for 3-3.49 nmol/L and HR = 2.40, 95% CI 1.24-4.66, p = 0.009 for >3.5 nmol/L). Mirroring this finding, SHBG <30 nmol/L was associated with increased NAFLD hazard (HR = 4.75, 95% CI 2.44-9.25, p < 0.001 for 20-29.99 nmol/L and HR = 4.98, 95% CI 2.45-10.11, p < 0.001 for <20 nmol/L). Limitations of this study include its retrospective nature, absence of detailed information on criteria used to diagnosis PCOS and NAFLD, and absence of data on laboratory assays used to measure serum androgens.Conclusions: We found that women with PCOS have an increased rate of NAFLD. In addition to increased BMI and dysglycemia, androgen excess contributes to the development of NAFLD in women with PCOS. In women with PCOS-related androgen excess, systematic NAFLD screening should be considered. [ABSTRACT FROM AUTHOR]

Background: Comorbidities are common in patients with heart failure (HF) and complicate treatment and outcomes. We identified patterns of multimorbidity in Asian patients with HF and their association with patients' quality of life (QoL) and health outcomes.Methods and Findings: We used data on 6,480 patients with chronic HF (1,204 with preserved ejection fraction) enrolled between 1 October 2012 and 6 October 2016 in the Asian Sudden Cardiac Death in Heart Failure (ASIAN-HF) registry. The ASIAN-HF registry is a prospective cohort study, with patients prospectively enrolled from in- and outpatient clinics from 11 Asian regions (Hong Kong, Taiwan, China, Japan, Korea, India, Malaysia, Thailand, Singapore, Indonesia, and Philippines). Latent class analysis was used to identify patterns of multimorbidity. The primary outcome was defined as a composite of all-cause mortality or HF hospitalization within 1 year. To assess differences in QoL, we used the Kansas City Cardiomyopathy Questionnaire. We identified 5 distinct multimorbidity groups: elderly/atrial fibrillation (AF) (N = 1,048; oldest, more AF), metabolic (N = 1,129; obesity, diabetes, hypertension), young (N = 1,759; youngest, low comorbidity rates, non-ischemic etiology), ischemic (N = 1,261; ischemic etiology), and lean diabetic (N = 1,283; diabetic, hypertensive, low prevalence of obesity, high prevalence of chronic kidney disease). Patients in the lean diabetic group had the worst QoL, more severe signs and symptoms of HF, and the highest rate of the primary combined outcome within 1 year (29% versus 11% in the young group) (p for all <0.001). Adjusting for confounders (demographics, New York Heart Association class, and medication) the lean diabetic (hazard ratio [HR] 1.79, 95% CI 1.46-2.22), elderly/AF (HR 1.57, 95% CI 1.26-1.96), ischemic (HR 1.51, 95% CI 1.22-1.88), and metabolic (HR 1.28, 95% CI 1.02-1.60) groups had higher rates of the primary combined outcome compared to the young group. Potential limitations include site selection and participation bias.Conclusions: Among Asian patients with HF, comorbidities naturally clustered in 5 distinct patterns, each differentially impacting patients' QoL and health outcomes. These data underscore the importance of studying multimorbidity in HF and the need for more comprehensive approaches in phenotyping patients with HF and multimorbidity.Trial Registration: ClinicalTrials.gov NCT01633398. [ABSTRACT FROM AUTHOR]

Background: Optimally treated heart failure (HF) patients often have persisting symptoms and poor health-related quality of life. Comorbidities are common, but little is known about their impact on these factors, and guideline-driven HF care remains focused on cardiovascular status. The following hypotheses were tested: (i) comorbidities are associated with more severe symptoms and functional limitations and subsequently worse patient-rated health in HF, and (ii) these patterns of association differ among selected comorbidities.Methods and Findings: The Swedish Heart Failure Registry (SHFR) is a national population-based register of HF patients admitted to >85% of hospitals in Sweden or attending outpatient clinics. This study included 10,575 HF patients with patient-rated health recorded during first registration in the SHFR (1 February 2008 to 1 November 2013). An a priori health model and sequences-of-regressions analysis were used to test associations among comorbidities and patient-reported symptoms, functional limitations, and patient-rated health. Patient-rated health measures included the EuroQol-5 dimension (EQ-5D) questionnaire and the EuroQol visual analogue scale (EQ-VAS). EQ-VAS score ranges from 0 (worst health) to 100 (best health). Patient-rated health declined progressively from patients with no comorbidities (mean EQ-VAS score, 66) to patients with cardiovascular comorbidities (mean EQ-VAS score, 62) to patients with non-cardiovascular comorbidities (mean EQ-VAS score, 59). The relationships among cardiovascular comorbidities and patient-rated health were explained by their associations with anxiety or depression (atrial fibrillation, odds ratio [OR] 1.16, 95% CI 1.06 to 1.27; ischemic heart disease [IHD], OR 1.20, 95% CI 1.09 to 1.32) and with pain (IHD, OR 1.25, 95% CI 1.14 to 1.38). Associations of non-cardiovascular comorbidities with patient-rated health were explained by their associations with shortness of breath (diabetes, OR 1.17, 95% CI 1.03 to 1.32; chronic kidney disease [CKD, OR 1.23, 95% CI 1.10 to 1.38; chronic obstructive pulmonary disease [COPD], OR 95% CI 1.84, 1.62 to 2.10) and with fatigue (diabetes, OR 1.27, 95% CI 1.13 to 1.42; CKD, OR 1.24, 95% CI 1.12 to 1.38; COPD, OR 1.69, 95% CI 1.50 to 1.91). There were direct associations between all symptoms and patient-rated health, and indirect associations via functional limitations. Anxiety or depression had the strongest association with functional limitations (OR 10.03, 95% CI 5.16 to 19.50) and patient-rated health (mean difference in EQ-VAS score, -18.68, 95% CI -23.22 to -14.14). HF optimizing therapies did not influence these associations. Key limitations of the study include the cross-sectional design and unclear generalisability to other populations. Further prospective HF studies are required to test the consistency of the relationships and their implications for health.Conclusions: Identification of distinct comorbidity health pathways in HF could provide the evidence for individualised person-centred care that targets specific comorbidities and associated symptoms. [ABSTRACT FROM AUTHOR]

Background: Cerebral white matter hyperintensities (WMHs) on MRI are common and associated with vascular and functional outcomes. However, the relationship between WMHs and longitudinal trajectories of functional status is not well characterized. We hypothesized that whole brain WMHs are associated with functional decline independently of intervening clinical vascular events and other vascular risk factors.Methods and Findings: In the Northern Manhattan Study (NOMAS), a population-based racially/ethnically diverse prospective cohort study, 1,290 stroke-free individuals underwent brain MRI and were followed afterwards for a mean 7.3 years with annual functional assessments using the Barthel index (BI) (range 0-100) and vascular event surveillance. Whole brain white matter hyperintensity volume (WMHV) (as percentage of total cranial volume [TCV]) was standardized and treated continuously. Generalized estimating equation (GEE) models tested associations between whole brain WMHV and baseline BI and change in BI, adjusting for sociodemographic, vascular, and cognitive risk factors, as well as stroke and myocardial infarction (MI) occurring during follow-up. Mean age was 70.6 (standard deviation [SD] 9.0) years, 40% of participants were male, 66% Hispanic; mean whole brain WMHV was 0.68% (SD 0.84). In fully adjusted models, annual functional change was -1.04 BI points (-1.20, -0.88), with -0.74 additional points annually per SD whole brain WMHV increase from the mean (-0.99, -0.49). Whole brain WMHV was not associated with baseline BI, and results were similar for mobility and non-mobility BI domains and among those with baseline BI 95-100. A limitation of the study is the possibility of a healthy survivor bias, which would likely have underestimated the associations we found.Conclusions: In this large population-based study, greater whole brain WMHV was associated with steeper annual decline in functional status over the long term, independently of risk factors, vascular events, and baseline functional status. Subclinical brain ischemic changes may be an independent marker of long-term functional decline. [ABSTRACT FROM AUTHOR]

Background: Clinical practice guidelines have traditionally recommended blood pressure treatment based primarily on blood pressure thresholds. In contrast, using predicted cardiovascular risk has been advocated as a more effective strategy to guide treatment decisions for cardiovascular disease (CVD) prevention. We aimed to compare outcomes from a blood pressure-lowering treatment strategy based on predicted cardiovascular risk with one based on systolic blood pressure (SBP) level.Methods and Findings: We used individual participant data from the Blood Pressure Lowering Treatment Trialists' Collaboration (BPLTTC) from 1995 to 2013. Trials randomly assigned participants to either blood pressure-lowering drugs versus placebo or more intensive versus less intensive blood pressure-lowering regimens. We estimated 5-y risk of CVD events using a multivariable Weibull model previously developed in this dataset. We compared the two strategies at specific SBP thresholds and across the spectrum of risk and blood pressure levels studied in BPLTTC trials. The primary outcome was number of CVD events avoided per persons treated. We included data from 11 trials (47,872 participants). During a median of 4.0 y of follow-up, 3,566 participants (7.5%) experienced a major cardiovascular event. Areas under the curve comparing the two treatment strategies throughout the range of possible thresholds for CVD risk and SBP demonstrated that, on average, a greater number of CVD events would be avoided for a given number of persons treated with the CVD risk strategy compared with the SBP strategy (area under the curve 0.71 [95% confidence interval (CI) 0.70-0.72] for the CVD risk strategy versus 0.54 [95% CI 0.53-0.55] for the SBP strategy). Compared with treating everyone with SBP ≥ 150 mmHg, a CVD risk strategy would require treatment of 29% (95% CI 26%-31%) fewer persons to prevent the same number of events or would prevent 16% (95% CI 14%-18%) more events for the same number of persons treated. Compared with treating everyone with SBP ≥ 140 mmHg, a CVD risk strategy would require treatment of 3.8% (95% CI 12.5% fewer to 7.2% more) fewer persons to prevent the same number of events or would prevent 3.1% (95% CI 1.5%-5.0%) more events for the same number of persons treated, although the former estimate was not statistically significant. In subgroup analyses, the CVD risk strategy did not appear to be more beneficial than the SBP strategy in patients with diabetes mellitus or established CVD.Conclusions: A blood pressure-lowering treatment strategy based on predicted cardiovascular risk is more effective than one based on blood pressure levels alone across a range of thresholds. These results support using cardiovascular risk assessment to guide blood pressure treatment decision-making in moderate- to high-risk individuals, particularly for primary prevention. [ABSTRACT FROM AUTHOR]

Background: Atrial fibrillation (AF) is the most commonly encountered arrhythmia and is associated with an elevated risk of stroke. Improving the identification of patients with the highest risk for AF to enable appropriate surveillance and treatment, if necessary, is critical to reducing AF-associated morbidity and mortality. Multiple common single nucleotide polymorphisms (SNPs) are unequivocally associated with the lifetime risk of AF. In the current study we aimed to prospectively validate an AF genetic risk score (GRS) in previously undiagnosed patients at risk for AF.Methods and Findings: Individuals 40 years of age or older with 1 clinical risk factor for AF, presenting with symptoms of AF, or with a first diagnosis of AF, were enrolled for genetic testing and ambulatory cardiac rhythm monitoring with an adhesive patch monitor or a long-term Holter monitor (mean wear time 10 days 21 hours and 13 days 18 hours, respectively). An AF event was the first diagnosis of AF by ECG, patch monitor, or long-term Holter monitor. The AF GRS was determined for each participant based on the weighted contribution of 12 genetic risk loci. Of 904 participants, 85 manifested AF. Their mean age was 66.2 (SD 11.8) years; 38% of participants were male. Participants in the highest quintile of AF GRS were more likely (odds ratio 3.11; 95% CI 1.27-7.58; p = 0.01) to have had an AF event than participants in the lowest quintile after adjusting for age, sex, smoking status, BMI, hypertension, diabetes mellitus, heart failure, and prior myocardial infarction. Study limitations included an ethnically homogenous population, a restricted rhythm monitoring period, and the evolving discovery of SNPs associated with AF.Conclusions: Prospective assessment of a GRS for AF identified participants with elevated risk of AF beyond established clinical criteria. Accordingly, a GRS for AF could be incorporated into overall risk assessment to better identify patients at the highest risk of developing AF, although further testing in larger populations is needed to confirm these findings.Trial Registration: ClinicalTrials.gov NCT01970969. [ABSTRACT FROM AUTHOR]

In a Perspective, Tammy Hoffmann and colleagues discuss medical decision making for elderly patients with multimorbidity. [ABSTRACT FROM AUTHOR]

Background: The prevalence of diabetes, heart disease, and stroke multimorbidity (co-occurrence of two or three of these conditions) has increased rapidly. Little is known about how the three conditions progress from one to another sequentially through the life course. We aimed to delineate this progression in middle-aged women and to determine the roles of common risk factors in the accumulation of diabetes, heart disease, and stroke multimorbidity.Methods and Findings: We used data from 13,714 women aged 45-50 years without a history of any of the three conditions. They were participants in the Australian Longitudinal Study on Women's Health (ALSWH), enrolled in 1996, and surveyed approximately every 3 years to 2016. We characterized the longitudinal progression of the three conditions and multimorbidity. We estimated the accumulation of multimorbidity over 20 years of follow-up and investigated their association with both baseline and time-varying predictors (sociodemographic factors, lifestyle factors, and other chronic conditions). Over 20 years, 2,511 (18.3%) of the women progressed to at least one condition, of whom 1,420 (56.6%) had diabetes, 1,277 (50.9%) had heart disease, and 308 (12.3%) had stroke; 423 (16.8%) had two or three of these conditions. Over a 3-year period, the age-adjusted odds of two or more conditions was approximately twice that of developing one new condition compared to women who did not develop any new conditions. For example, the odds for developing one new condition between Surveys 7 and 8 were 2.29 (95% confidence interval [CI], 1.93-2.72), whereas the odds for developing two or more conditions was 6.51 (95% CI, 3.95-10.75). The onset of stroke was more strongly associated with the progression to the other conditions (i.e., 23.4% [95% CI, 16.3%-32.2%] of women after first onset of stroke progressed to other conditions, whereas the percentages for diabetes and heart disease were 9.9% [95% CI, 7.9%-12.4%] and 11.4% [95% CI, 9.1%-14.4%], respectively). Being separated, divorced, or widowed; being born outside Australia; having difficulty managing on their available income; being overweight or obese; having hypertension; being physically inactive; being a current smoker; and having prior chronic conditions (i.e., mental disorders, asthma, cancer, osteoporosis, and arthritis) were significantly associated with increased odds of accumulation of diabetes, heart disease, and stroke multimorbidity. The main limitations of this study were the use of self-reported data and the low number of events.Conclusions: Stroke was associated with increased risk of progression to diabetes or heart disease. Social inequality, obesity, hypertension, physical inactivity, smoking, or having other chronic conditions were also significantly associated with increased odds of accumulating multimorbidity. Our findings highlight the importance of awareness of the role of diabetes, heart disease, and stroke multimorbidity among middle-aged women for clinicians and health-promotion agencies. [ABSTRACT FROM AUTHOR]

Background: Multimorbidity in people with cardiovascular disease (CVD) is common, but large-scale contemporary reports of patterns and trends in patients with incident CVD are limited. We investigated the burden of comorbidities in patients with incident CVD, how it changed between 2000 and 2014, and how it varied by age, sex, and socioeconomic status (SES).Methods and Findings: We used the UK Clinical Practice Research Datalink with linkage to Hospital Episode Statistics, a population-based dataset from 674 UK general practices covering approximately 7% of the current UK population. We estimated crude and age/sex-standardised (to the 2013 European Standard Population) prevalence and 95% confidence intervals for 56 major comorbidities in individuals with incident non-fatal CVD. We further assessed temporal trends and patterns by age, sex, and SES groups, between 2000 and 2014. Among a total of 4,198,039 people aged 16 to 113 years, 229,205 incident cases of non-fatal CVD, defined as first diagnosis of ischaemic heart disease, stroke, or transient ischaemic attack, were identified. Although the age/sex-standardised incidence of CVD decreased by 34% between 2000 to 2014, the proportion of CVD patients with higher numbers of comorbidities increased. The prevalence of having 5 or more comorbidities increased 4-fold, rising from 6.3% (95% CI 5.6%-17.0%) in 2000 to 24.3% (22.1%-34.8%) in 2014 in age/sex-standardised models. The most common comorbidities in age/sex-standardised models were hypertension (28.9% [95% CI 27.7%-31.4%]), depression (23.0% [21.3%-26.0%]), arthritis (20.9% [19.5%-23.5%]), asthma (17.7% [15.8%-20.8%]), and anxiety (15.0% [13.7%-17.6%]). Cardiometabolic conditions and arthritis were highly prevalent among patients aged over 40 years, and mental illnesses were highly prevalent in patients aged 30-59 years. The age-standardised prevalence of having 5 or more comorbidities was 19.1% (95% CI 17.2%-22.7%) in women and 12.5% (12.0%-13.9%) in men, and women had twice the age-standardised prevalence of depression (31.1% [28.3%-35.5%] versus 15.0% [14.3%-16.5%]) and anxiety (19.6% [17.6%-23.3%] versus 10.4% [9.8%-11.8%]). The prevalence of depression was 46% higher in the most deprived fifth of SES compared with the least deprived fifth (age/sex-standardised prevalence of 38.4% [31.2%-62.0%] versus 26.3% [23.1%-34.5%], respectively). This is a descriptive study of routine electronic health records in the UK, which might underestimate the true prevalence of diseases.Conclusions: The burden of multimorbidity and comorbidity in patients with incident non-fatal CVD increased between 2000 and 2014. On average, older patients, women, and socioeconomically deprived groups had higher numbers of comorbidities, but the type of comorbidities varied by age and sex. Cardiometabolic conditions contributed substantially to the burden, but 4 out of the 10 top comorbidities were non-cardiometabolic. The current single-disease paradigm in CVD management needs to broaden and incorporate the large and increasing burden of comorbidities. [ABSTRACT FROM AUTHOR]

Background: Migrant and ethnic minority groups are often assumed to have poor health relative to the majority population. Few countries have the capacity to study a key indicator, mortality, by ethnicity and country of birth. We hypothesized at least 10% differences in mortality by ethnic group in Scotland that would not be wholly attenuated by adjustment for socio-economic factors or country of birth.Methods and Findings: We linked the Scottish 2001 Census to mortality data (2001-2013) in 4.62 million people (91% of estimated population), calculating age-adjusted mortality rate ratios (RRs; multiplied by 100 as percentages) with 95% confidence intervals (CIs) for 13 ethnic groups, with the White Scottish group as reference (ethnic group classification follows the Scottish 2001 Census). The Scottish Index of Multiple Deprivation, education status, and household tenure were socio-economic status (SES) confounding variables and born in the UK or Republic of Ireland (UK/RoI) an interacting and confounding variable. Smoking and diabetes data were from a primary care sub-sample (about 53,000 people). Males and females in most minority groups had lower age-adjusted mortality RRs than the White Scottish group. The 95% CIs provided good evidence that the RR was more than 10% lower in the following ethnic groups: Other White British (72.3 [95% CI 64.2, 81.3] in males and 75.2 [68.0, 83.2] in females); Other White (80.8 [72.8, 89.8] in males and 76.2 [68.6, 84.7] in females); Indian (62.6 [51.6, 76.0] in males and 60.7 [50.4, 73.1] in females); Pakistani (66.1 [57.4, 76.2] in males and 73.8 [63.7, 85.5] in females); Bangladeshi males (50.7 [32.5, 79.1]); Caribbean females (57.5 [38.5, 85.9]); and Chinese (52.2 [43.7, 62.5] in males and 65.8 [55.3, 78.2] in females). The differences were diminished but not eliminated after adjusting for UK/RoI birth and SES variables. A mortality advantage was evident in all 12 minority groups for those born abroad, but in only 6/12 male groups and 5/12 female groups of those born in the UK/RoI. In the primary care sub-sample, after adjustment for age, UK/RoI born, SES, smoking, and diabetes, the RR was not lower in Indian males (114.7 [95% CI 78.3, 167.9]) and Pakistani females (103.9 [73.9, 145.9]) than in White Scottish males and females, respectively. The main limitations were the inability to include deaths abroad and the small number of deaths in some ethnic minority groups, especially for people born in the UK/RoI.Conclusions: There was relatively low mortality for many ethnic minority groups compared to the White Scottish majority. The mortality advantage was less clear in UK/RoI-born minority group offspring than in immigrants. These differences need explaining, and health-related behaviours seem important. Similar analyses are required internationally to fulfil agreed goals for monitoring, understanding, and improving health in ethnically diverse societies and to apply to health policy, especially on health inequalities and inequities. [ABSTRACT FROM AUTHOR]

Background: Gestational diabetes mellitus (GDM) is associated with developing type 2 diabetes, but very few studies have examined its effect on developing cardiovascular disease.Methods and Findings: We conducted a retrospective cohort study utilizing a large primary care database in the United Kingdom. From 1 February 1990 to 15 May 2016, 9,118 women diagnosed with GDM were identified and randomly matched with 37,281 control women by age and timing of pregnancy (up to 3 months). Adjusted incidence rate ratios (IRRs) with 95% confidence intervals (CIs) were calculated for cardiovascular risk factors and cardiovascular disease. Women with GDM were more likely to develop type 2 diabetes (IRR = 21.96; 95% CI 18.31-26.34) and hypertension (IRR = 1.85; 95% CI 1.59-2.16) after adjusting for age, Townsend (deprivation) quintile, body mass index, and smoking. For ischemic heart disease (IHD), the IRR was 2.78 (95% CI 1.37-5.66), and for cerebrovascular disease 0.95 (95% CI 0.51-1.77; p-value = 0.87), after adjusting for the above covariates and lipid-lowering medication and hypertension at baseline. Follow-up screening for type 2 diabetes and cardiovascular risk factors was poor. Limitations include potential selective documentation of severe GDM for women in primary care, higher surveillance for outcomes in women diagnosed with GDM than control women, and a short median follow-up postpartum period, with a small number of outcomes for IHD and cerebrovascular disease.Conclusions: Women diagnosed with GDM were at very high risk of developing type 2 diabetes and had a significantly increased incidence of hypertension and IHD. Identifying this group of women in general practice and targeting cardiovascular risk factors could improve long-term outcomes. [ABSTRACT FROM AUTHOR]

Background: In the United Kingdom, the Food Standards Agency-Ofcom nutrient profiling model (FSA-Ofcom model) is used to define less-healthy foods that cannot be advertised to children. However, there has been limited investigation of whether less-healthy foods defined by this model are associated with prospective health outcomes. The objective of this study was to test whether consumption of less-healthy food as defined by the FSA-Ofcom model is associated with cardiovascular disease (CVD).Methods and Findings: We used data from the European Prospective Investigation of Cancer (EPIC)-Norfolk cohort study in adults (n = 25,639) aged 40-79 years who completed a 7-day diet diary between 1993 and 1997. Incident CVD (primary outcome), cardiovascular mortality, and all-cause mortality (secondary outcomes) were identified using record linkage to hospital admissions data and death certificates up to 31 March 2015. Each food and beverage item reported was coded and given a continuous score, using the FSA-Ofcom model, based on the consumption of energy; saturated fat; total sugar; sodium; nonsoluble fibre; protein; and fruits, vegetables, and nuts. Items were classified as less-healthy using Ofcom regulation thresholds. We used Cox proportional hazards regression to test for an association between consumption of less-healthy food and incident CVD. Sensitivity analyses explored whether the results differed based on the definition of the exposure. Analyses were adjusted for age, sex, behavioural risk factors, clinical risk factors, and socioeconomic status. Participants were followed up for a mean of 16.4 years. During follow-up, there were 4,965 incident cases of CVD (1,524 fatal within 30 days). In the unadjusted analyses, we observed an association between consumption of less-healthy food and incident CVD (test for linear trend over quintile groups, p < 0.01). After adjustment for covariates (sociodemographic, behavioural, and indices of cardiovascular risk), we found no association between consumption of less-healthy food and incident CVD (p = 0.84) or cardiovascular mortality (p = 0.90), but there was an association between consumption of less-healthy food and all-cause mortality (test for linear trend, p = 0.006; quintile group 5, highest consumption of less-healthy food, versus quintile group 1, HR = 1.11, 95% CI 1.02-1.20). Sensitivity analyses produced similar results. The study is observational and relies on self-report of dietary consumption. Despite adjustment for known and reported confounders, residual confounding is possible.Conclusions: After adjustment for potential confounding factors, no significant association between consumption of less-healthy food (as classified by the FSA-Ofcom model) and CVD was observed in this study. This suggests, in the UK setting, that the FSA-Ofcom model is not consistently discriminating among foods with respect to their association with CVD. More studies are needed to understand better the relationship between consumption of less-healthy food, defined by the FSA-Ofcom model, and indices of health. [ABSTRACT FROM AUTHOR]

Background: The Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) study has developed predictive risk scores for cardiovascular disease (CVD) and chronic kidney disease (CKD, defined as confirmed estimated glomerular filtration rate [eGFR] ≤ 60 ml/min/1.73 m2) events in HIV-positive people. We hypothesized that participants in D:A:D at high (>5%) predicted risk for both CVD and CKD would be at even greater risk for CVD and CKD events.Methods and Findings: We included all participants with complete risk factor (covariate) data, baseline eGFR > 60 ml/min/1.73 m2, and a confirmed (>3 months apart) eGFR < 60 ml/min/1.73 m2 thereafter to calculate CVD and CKD risk scores. We calculated CVD and CKD event rates by predicted 5-year CVD and CKD risk groups (≤1%, >1%-5%, >5%) and fitted Poisson models to assess whether CVD and CKD risk group effects were multiplicative. A total of 27,215 participants contributed 202,034 person-years of follow-up: 74% male, median (IQR) age 42 (36, 49) years, median (IQR) baseline year of follow-up 2005 (2004, 2008). D:A:D risk equations predicted 3,560 (13.1%) participants at high CVD risk, 4,996 (18.4%) participants at high CKD risk, and 1,585 (5.8%) participants at both high CKD and high CVD risk. CVD and CKD event rates by predicted risk group were multiplicative. Participants at high CVD risk had a 5.63-fold (95% CI 4.47, 7.09, p < 0.001) increase in CKD events compared to those at low risk; participants at high CKD risk had a 1.31-fold (95% CI 1.09, 1.56, p = 0.005) increase in CVD events compared to those at low risk. Participants' CVD and CKD risk groups had multiplicative predictive effects, with no evidence of an interaction (p = 0.329 and p = 0.291 for CKD and CVD, respectively). The main study limitation is the difference in the ascertainment of the clinically defined CVD endpoints and the laboratory-defined CKD endpoints.Conclusions: We found that people at high predicted risk for both CVD and CKD have substantially greater risks for both CVD and CKD events compared with those at low predicted risk for both outcomes, and compared to those at high predicted risk for only CVD or CKD events. This suggests that CVD and CKD risk in HIV-positive persons should be assessed together. The results further encourage clinicians to prioritise addressing modifiable risks for CVD and CKD in HIV-positive people. [ABSTRACT FROM AUTHOR]

Ronald Ma and Barry Popkin discuss the urgent need and challenges to reduce intergenerational transmission of obesity and diabetes. [ABSTRACT FROM AUTHOR]

Background: To reduce over-diagnosis of chronic kidney disease (CKD) resulting from the inaccuracy of creatinine-based estimates of glomerular filtration rate (GFR), UK and international guidelines recommend that cystatin-C-based estimates of GFR be used to confirm or exclude the diagnosis in people with GFR 45-59 ml/min/1.73 m2 and no albuminuria (CKD G3aA1). Whilst there is good evidence for cystatin C being a marker of GFR and risk in people with CKD, its use to define CKD in this manner has not been evaluated in primary care, the setting in which most people with GFR in this range are managed.Methods and Findings: A total of 1,741 people with CKD G3a or G3b defined by 2 estimated GFR (eGFR) values more than 90 days apart were recruited to the Renal Risk in Derby study between June 2008 and March 2010. Using Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations, we compared GFR estimated from creatinine (eGFRcreat), cystatin C (eGFRcys), and both (eGFRcreat-cys) at baseline and over 5 years of follow-up. We analysed the proportion of participants with CKD G3aA1 reclassified to 'no CKD' or more advanced CKD with the latter two equations. We further assessed the impact of using cystatin-C-based eGFR in risk prediction equations for CKD progression and all-cause mortality and investigated non-GFR determinants of eGFRcys. Finally, we estimated the cost implications of implementing National Institute for Health and Care Excellence (NICE) guidance to use eGFRcys to confirm the diagnosis in people classified as CKD G3aA1 by eGFRcreat. Mean eGFRcys was significantly lower than mean eGFRcreat (45.1 ml/min/1.73 m2, 95% CI 44.4 to 45.9, versus 53.6 ml/min/1.73 m2, 95% CI 53.0 to 54.1, P < 0.001). eGFRcys reclassified 7.7% (50 of 653) of those with CKD G3aA1 by eGFRcreat to eGFR ≥ 60 ml/min/1.73 m2. However, a much greater proportion (59.0%, 385 of 653) were classified to an eGFR category indicating more severe CKD. A similar pattern was seen using eGFRcreat-cys, but lower proportions were reclassified. Change in eGFRcreat and eGFRcys over 5 years were weakly correlated (r = 0.33, P < 0.001), but eGFRcys identified more people as having CKD progression (18.2% versus 10.5%). Multivariable analysis using eGFRcreat as an independent variable identified age, smoking status, body mass index, haemoglobin, serum uric acid, serum albumin, albuminuria, and C reactive protein as non-GFR determinants of eGFRcys. Use of eGFRcys or eGFRcreat-cys did not improve discrimination in risk prediction models for CKD progression and all-cause mortality compared to similar models with eGFRcreat. Application of the NICE guidance, which assumed cost savings, to participants with CKD G3aA1 increased the cost of monitoring by £23 per patient, which if extrapolated to be applied throughout England would increase the cost of testing and monitoring CKD by approximately £31 million per year. Limitations of this study include the lack of a measured GFR and the potential lack of ethnic diversity in the study cohort.Conclusions: Implementation of current guidelines on eGFRcys testing in our study population of older people in primary care resulted in only a small reduction in diagnosed CKD but classified a greater proportion as having more advanced CKD than eGFRcreat. Use of eGFRcys did not improve risk prediction in this population and was associated with increased cost. Our data therefore do not support implementation of these recommendations in primary care. Further studies are warranted to define the most appropriate clinical application of eGFRcys and eGFRcreat-cys. [ABSTRACT FROM AUTHOR]

Background: Combinations of multiple fatty acids may influence cardiometabolic risk more than single fatty acids. The association of a combination of fatty acids with incident type 2 diabetes (T2D) has not been evaluated.Methods and Findings: We measured plasma phospholipid fatty acids by gas chromatography in 27,296 adults, including 12,132 incident cases of T2D, over the follow-up period between baseline (1991-1998) and 31 December 2007 in 8 European countries in EPIC-InterAct, a nested case-cohort study. The first principal component derived by principal component analysis of 27 individual fatty acids (mole percentage) was the main exposure (subsequently called the fatty acid pattern score [FA-pattern score]). The FA-pattern score was partly characterised by high concentrations of linoleic acid, stearic acid, odd-chain fatty acids, and very-long-chain saturated fatty acids and low concentrations of γ-linolenic acid, palmitic acid, and long-chain monounsaturated fatty acids, and it explained 16.1% of the overall variability of the 27 fatty acids. Based on country-specific Prentice-weighted Cox regression and random-effects meta-analysis, the FA-pattern score was associated with lower incident T2D. Comparing the top to the bottom fifth of the score, the hazard ratio of incident T2D was 0.23 (95% CI 0.19-0.29) adjusted for potential confounders and 0.37 (95% CI 0.27-0.50) further adjusted for metabolic risk factors. The association changed little after adjustment for individual fatty acids or fatty acid subclasses. In cross-sectional analyses relating the FA-pattern score to metabolic, genetic, and dietary factors, the FA-pattern score was inversely associated with adiposity, triglycerides, liver enzymes, C-reactive protein, a genetic score representing insulin resistance, and dietary intakes of soft drinks and alcohol and was positively associated with high-density-lipoprotein cholesterol and intakes of polyunsaturated fat, dietary fibre, and coffee (p < 0.05 each). Limitations include potential measurement error in the fatty acids and other model covariates and possible residual confounding.Conclusions: A combination of individual fatty acids, characterised by high concentrations of linoleic acid, odd-chain fatty acids, and very long-chain fatty acids, was associated with lower incidence of T2D. The specific fatty acid pattern may be influenced by metabolic, genetic, and dietary factors. [ABSTRACT FROM AUTHOR]