Lifestyle patterns and incident type 2 diabetes in the Dutch lifelines cohort study

We aimed to identify the underlying subgroups of the population characterized by distinct lifestyle patterns, and to investigate the associations between lifestyle patterns and risk of incident type 2 diabetes. Using data from the Dutch Lifelines cohort study, latent class analysis was performed to derive lifestyle patterns on five lifestyle factors, i.e., smoking, diet quality, TV watching time, physical activity level, and risk drinking. Associations between lifestyle patterns and incident type 2 diabetes were estimated. Among 61,869 participants analyzed, we identified 900 cases of type 2 diabetes during follow-up (205,696 person-years; incidence rate 4.38 per 1000 person-years). Five lifestyle pattern groups were identified. Using the “healthy lifestyle group” as reference, the “unhealthy lifestyle group” had the highest risk for type 2 diabetes (HR 1.51 [95%CI 1.24, 1.85]), followed by the “poor diet and low physical activity group” (HR 1.26 [95%CI 1.03, 1.55]). The “risk drinker group” and the “couch potato group” (characterized by excessive TV watching) showed no significantly elevated risk. These models were adjusted for age, sex, total energy intake, education, BMI, family history of diabetes, and blood glucose level at baseline. Our study shows that lifestyle factors tended to cluster in unique behavioral patterns within the heterogeneous population. These lifestyle patterns were differentially associated with incident type 2 diabetes. Our findings support the relevance of considering lifestyle patterns in type 2 diabetes prevention. Tailored prevention strategies that target multiple lifestyle risk factors for different lifestyle pattern groups may optimize the effectiveness of diabetes prevention at the population level

Effect of selective serotonin reuptake inhibitor treatment following diagnosis of depression on suicidal behaviour risk: a target trial emulation

There is concern regarding the impact of selective serotonin reuptake inhibitors (SSRIs) on suicidal behaviour. Using the target trial framework, we investigated the effect on suicidal behaviour of SSRI treatment following a depression diagnosis. We identified 162,267 individuals receiving a depression diagnosis aged 6–59 years during 2006–2018 in Stockholm County, Sweden, after at least 1 year without antidepressant dispensation. Individuals who initiated an SSRI within 28 days of the diagnosis were assigned as SSRI initiators, others as non-initiators. Intention-to-treat and per-protocol effects were estimated; for the latter, individuals were censored when they ceased adhering to their assigned treatment strategy. We applied inverse probability weighting (IPW) to account for baseline confounding in the intention-to-treat analysis, and additionally for treatment non-adherence and time-varying confounding in the per-protocol analysis. The suicidal behaviour risk difference (RD), and risk ratio (RR) between SSRI initiators and non-initiators were estimated at 12 weeks. In the overall cohort, we found an increased risk of suicidal behaviour among SSRI initiators (intention-to-treat RR = 1.50, 95% CI = 1.25, 1.80; per-protocol RR = 1.69, 95% CI = 1.20, 2.36). In age strata, we only found evidence of an increased risk among individuals under age 25, with the greatest risk among 6–17-year-olds (intention-to-treat RR = 2.90, 95% CI = 1.72, 4.91; per-protocol RR = 3.34, 95% CI = 1.59, 7.00). Our finding of an increased suicidal behaviour risk among individuals under age 25 reflects evidence from RCTs. We found no evidence of an effect in the high-risk group of individuals with past suicidal behaviour. Further studies with information on a wider array of confounders are called for

Medical Nutritional Therapy for Patients with Chronic Kidney Disease not on Dialysis: The Low Protein Diet as a Medication

The 2020 Kidney Disease Outcome Quality Initiative (KDOQI) Clinical Practice Guideline for Nutrition in chronic kidney disease (CKD) recommends protein restriction to patients affected by CKD in stages 3 to 5 (not on dialysis), provided that they are metabolically stable, with the goal to delay kidney failure (graded as evidence level 1A) and improve quality of life (graded as evidence level 2C). Despite these strong statements, low protein diets (LPDs) are not prescribed by many nephrologists worldwide. In this review, we challenge the view of protein restriction as an "option" in the management of patients with CKD, and defend it as a core element of care. We argue that LPDs need to be tailored and patient-centered to ensure adherence, efficacy, and safety. Nephrologists, aligned with renal dietitians, may approach the implementation of LPDs similarly to a drug prescription, considering its indications, contra-indications, mechanism of action, dosages, unwanted side effects, and special warnings. Following this framework, we discuss herein the benefits and potential harms of LPDs as a cornerstone in CKD management

Separate and combined effects of individual and neighbourhood socio-economic disadvantage on health-related lifestyle risk factors:a multilevel analysis

BACKGROUND: Socio-economic disadvantage at both individual and neighbourhood levels has been found to be associated with single lifestyle risk factors. However, it is unknown to what extent their combined effects contribute to a broad lifestyle profile. We aimed to (i) investigate the associations of individual socio-economic disadvantage (ISED) and neighbourhood socio-economic disadvantage (NSED) in relation to an extended score of health-related lifestyle risk factors (lifestyle risk index); and to (ii) investigate whether NSED modified the association between ISED and the lifestyle risk index. METHODS: Of 77 244 participants [median age (IQR): 46 (40-53) years] from the Lifelines cohort study in the northern Netherlands, we calculated a lifestyle risk index by scoring the lifestyle risk factors including smoking status, alcohol consumption, diet quality, physical activity, TV-watching time and sleep time. A higher lifestyle risk index was indicative of an unhealthier lifestyle. Composite scores of ISED and NSED based on a variety of socio-economic indicators were calculated separately. Linear mixed-effect models were used to examine the association of ISED and NSED with the lifestyle risk index and to investigate whether NSED modified the association between ISED and the lifestyle risk index by including an interaction term between ISED and NSED. RESULTS: Both ISED and NSED were associated with an unhealthier lifestyle, because ISED and NSED were both positively associated with the lifestyle risk index {highest quartile [Q4] ISED beta-coefficient [95% confidence interval (CI)]: 0.64 [0.62-0.66], P < 0.001; highest quintile [Q5] NSED beta-coefficient [95% CI]: 0.17 [0.14-0.21], P < 0.001} after adjustment for age, sex and body mass index. In addition, a positive interaction was found between NSED and ISED on the lifestyle risk index (beta-coefficient 0.016, 95% CI: 0.011-0.021, Pinteraction < 0.001), which indicated that NSED modified the association between ISED and the lifestyle risk index; i.e. the gradient of the associations across all ISED quartiles (Q4 vs Q1) was steeper among participants residing in the most disadvantaged neighbourhoods compared with those who resided in the less disadvantaged neighbourhoods. CONCLUSIONS: Our findings suggest that public health initiatives addressing lifestyle-related socio-economic health differences should not only target individuals, but also consider neighbourhood factors

Ultraprocessed food consumption and kidney function decline in a population-based cohort in the Netherlands

BACKGROUND: Ultra-processing makes food products more convenient, appealing, and profitable. Recent studies show that high ultra-processed food (UPF) intake is associated with the cardio-metabolic disease. OBJECTIVES: The aim of this study is to investigate the association between UPF consumption and risk of kidney function decline in the general population. METHODS: In a prospective general population-based Lifelines cohort from Northern Netherlands, 78 346 participants free of chronic kidney disease (CKD) at baseline responded to a 110-item food frequency questionnaire. We used multivariable regression analysis to study the association of the proportion (in gram/day) of UPF in the total diet with a composite kidney outcome (incident CKD or a ≥ 30% eGFR decline relative to baseline) and annual change in estimated glomerular filtration rate (eGFR). RESULTS: On average, 37.7% of total food intake came from UPF. After 3.6 ± 0.9 years of follow-up, 2 470 participants (3.2%) reached the composite kidney outcome. Participants in the highest quartile of UPF consumption were associated with a higher risk of the composite kidney outcome (OR 1.27, [95% CI: 1.09, 1.47], P = 0.003) compared with those in the lowest quartile, regardless of macro/micronutrient intake or diet quality. Participants in the highest quartile had a more rapid eGFR decline (β -0.17, [95% CI: -0.23, -0.11], P < 0.001) compared with those in the lowest quartile. Associations were generally consistent across different subgroups. CONCLUSIONS: Higher UPF consumption was associated with a higher risk of a composite kidney outcome (incident CKD or ≥ 30% eGFR decline) and a more rapid eGFR decline in the general population, independent of confounders and other dietary indices

Healthcare resource utilisation and related costs of patients with CKD from the UK: a report from the DISCOVER CKD retrospective cohort

Background Chronic kidney disease (CKD) is widely reported to decrease quality of life, increase morbidity and mortality and cause increased healthcare resource utilisation (HCRU) as the disease progresses. However, there is a relative paucity of accurate and recent estimates of HCRU in this patient population. Our aim was to address this evidence gap by reporting HCRU and related costs in patients with CKD from the UK primary and secondary care settings. Methods HCRU and cost estimates of CKD were derived for UK patients included in the DISCOVER CKD cohort study using clinical records from the Clinical Practice Research Datalink linked to external databases. Patients with a history of transplant or undergoing dialysis were not included. HCRU and costs were stratified by CKD severity using the urinary albumin:creatinine ratio (UACR) and estimated glomerular filtration rate. Results Hospitalisation rates more than tripled between low (A1) and high (A3) UACR categories and the mean annual per-patient costs ranged from £4966 (A1) to £9196 (A3) and from £4997 (G2) to £7595 (G5), demonstrating that a large healthcare burden can be attributed to a relatively small number of patients with later stage CKD, including those with kidney failure and/or albuminuria. Conclusions HCRU and costs associated with CKD impose a substantial burden on the healthcare system, particularly in the more advanced stages of CKD. New interventions that can delay the progression of CKD to kidney failure may not only prolong the patient’s life, but would also provide significant resource and cost savings to healthcare providers

Glucose-lowering treatment pathways of individuals with chronic kidney disease and type 2 diabetes according to the Kidney Disease: Improving Global Outcomes 2012 risk classification

Aims: To describe treatment pathways for key glucose-lowering therapies in individuals with chronic kidney disease (CKD) and type 2 diabetes (T2D) using retrospective data from DISCOVER CKD (NCT04034992). // Methods: Data were extracted from the UK Clinical Practice Research Datalink (CPRD) linked to Hospital Episode Statistics data (2008–2020) and the US integrated Limited Claims and Electronic Health Records Database (LCED; 2012–2019). Eligible individuals were aged ≥18 years with CKD, identified by two consecutive estimated glomerular filtration rate (eGFR) measures (15–<75 mL/min/1.73 m2; 90–730 days apart; index date was the second measurement) and T2D. Chronological treatment pathways for glucose-lowering therapies prescribed on or after CKD index to end of follow-up were computed. Median time and proportion of overall follow-up time on treatment were described for each therapy by database and by eGFR and urinary albumin-to-creatinine ratio (UACR) categories. // Results: Of 36,951 and 4339 eligible individuals in the CPRD and LCED, respectively, median baseline eGFR was 67.8 and 64.9 mL/min/1.73 m2; 64.2 and 63.9% received metformin prior to index; and median (interquartile range) time on metformin during follow-up was 917 (390–1671) and 454 (192–850) days (accounting for ~75% of follow-up time in both databases). The frequency of combination treatment increased over time. There were trends towards decreased metformin prescriptions with decreasing eGFR and increasing UACR within each eGFR category. // Conclusions: Individuals with CKD and T2D had many combinations of therapies and substantial follow-up time on therapy. These results highlight opportunities for improved CKD management