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.

Ultra-processed foods and risk of all-cause mortality in renal transplant recipients.

BACKGROUND: Renal transplant recipients (RTRs) have a 6-fold higher risk of mortality than age- and sex-matched controls. Whether high consumption of ultra-processed foods is associated with survival in RTRs is unknown. OBJECTIVES: We aimed to study the association between high consumption of ultra-processed foods and all-cause mortality in stable RTRs. METHODS: We conducted a prospective cohort study in adult RTRs with a stable graft. Dietary intake was assessed using a validated 177-item FFQ. Food items were categorized according to the NOVA classification system and the proportion ultra-processed foods comprised of total food weight per day was calculated. RESULTS: We included 632 stable RTRs (mean ± SD age: 53.0 ± 12.7 y, 57% men). Mean ± SD consumption of ultra-processed foods was 721 ± 341 g/d (28% of total weight of food intake), whereas the intake of unprocessed and minimally processed foods, processed culinary ingredients, and processed foods accounted for 57%, 1%, and 14%, respectively. During median follow-up of 5.4 y [IQR: 4.9-6.0 y], 129 (20%) RTRs died. In Cox regression analyses, ultra-processed foods were associated with all-cause mortality (HR per doubling of percentage of total weight: 2.13; 95% CI: 1.46, 3.10; P < 0.001), independently of potential confounders. This association was independent from the quality of the overall dietary pattern, expressed by the Mediterranean Diet Score (MDS) or Dietary Approaches to Stop Hypertension (DASH) score. When analyzing ultra-processed foods by groups, only sugar-sweetened beverages (HR: 1.21; 95% CI: 1.05, 1.39; P = 0.007), desserts (HR: 1.24; 95% CI: 1.02, 1.49; P = 0.03), and processed meats (HR: 1.87; 95% CI: 1.22, 2.86; P = 0.004) were associated with all-cause mortality. CONCLUSIONS: Consumption of ultra-processed foods, in particular sugar-sweetened beverages, desserts, and processed meats, is associated with a higher risk of all-cause mortality after renal transplantation, independently of low adherence to high-quality dietary patterns, such as the Mediterranean diet and the DASH diet.This trial was registered at clinicaltrials.gov as NCT02811835.

Effects of Education and Income on Incident Type 2 Diabetes and Cardiovascular Diseases: a Dutch Prospective Study.

BACKGROUND: Education and income, as two primary socioeconomic indicators, are often used interchangeably in health research. However, there is a lack of clear distinction between these two indicators concerning their associations with health. OBJECTIVE: This study aimed to investigate the separate and combined effects of education and income in relation to incident type 2 diabetes and cardiovascular diseases in the general population. DESIGN AND PARTICIPANTS: Participants aged between 30 and 65 years from the prospective Dutch Lifelines cohort study were included. Two sub-cohorts were subsequently created, including 83,759 and 91,083 participants for a type 2 diabetes cohort and a cardiovascular diseases cohort, respectively. MAIN MEASURES: Education and income level were assessed by self-report questionnaires. The outcomes were incident type 2 diabetes and cardiovascular diseases (defined as the earliest non-fatal cardiovascular event). KEY RESULTS: A total of 1228 new cases of type 2 diabetes (incidence 1.5%) and 3286 (incidence 3.6%) new cases of cardiovascular diseases were identified, after a median follow-up of 43 and 44 months, respectively. Low education and low income (<1000 euro/month) were both positively associated with a higher risk of incident type 2 diabetes (OR 1.24 [95%CI 1.04-1.48] and OR 1.71 [95%CI 1.30-2.26], respectively); and with a higher risk of incident cardiovascular diseases (OR 1.15 [95%CI 1.04-1.28] and OR 1.24 [95%CI 1.02-1.52], respectively); independent of age, sex, lifestyle factors, BMI, clinical biomarkers, comorbid conditions at baseline, and each other. Results from the combined associations of education and income showed that within each education group, a higher income was associated with better health; and similarly, a higher education was associated with better health within each income group, except for the low-income group. CONCLUSIONS: Education and income were both independently associated with incident type 2 diabetes and cardiovascular diseases. The combined associations of these two socioeconomic indicators revealed that within each education or income level, substantial health disparities existed across strata of the other socioeconomic indicator. Education and income are two equally important socioeconomic indicators in health, and should be considered simultaneously in health research and policymaking.

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

BACKGROUND: Ultraprocessing makes food products more convenient, appealing, and profitable. Recent studies show that high ultraprocessed food (UPF) intake is associated with cardiometabolic diseases. OBJECTIVES: The aim of this study is to investigate the association between UPF consumption and risks 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 FFQ. We used a multivariable regression analysis to study the associations of the proportion (in grams/day) of UPFs in the total diet with a composite kidney outcome [incident CKD or a ≥30% estimated glomerular filtration rate (eGFR) decline relative to baseline] and annual change in eGFR. RESULTS: On average, 37.7% of total food intake came from UPFs. After 3.6 ± 0.9 years of follow-up, 2470 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 their macro- or micronutrient intake or diet quality. Participants in the highest quartile had a more rapid eGFR decline (ß, -0.17; 95% CI, -0.23 to -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.

Using Structural Equation Modeling to Untangle Pathways of Risk Factors Associated with Incident Type 2 Diabetes: the Lifelines Cohort Study.

Risk factors for type 2 diabetes are multifaceted and interrelated. Unraveling the complex pathways of modifiable risk factors related to incident type 2 diabetes will help prioritize prevention targets. The current analysis extended a previously proposed conceptual model by Bardenheier et al. (Diabetes Care, 36(9), 2655-2662, 2013) on prediabetes with a cross-sectional design. The model described the pathways of four aspects of modifiable risk factors in relation to incident type 2 diabetes, including socioeconomic status (income and education); lifestyle behaviors (diet quality, physical activity, TV watching, smoking, risk drinking, and unhealthy sleep duration); clinical markers (HDL-cholesterol, triglycerides, BMI, and waist circumference); and blood pressure. We performed structural equation modeling to test this conceptual model using a prospective population-based sample of 68,649 participants (35-80 years) from the Lifelines cohort study. During a median follow-up of 41 months, 1124 new cases of type 2 diabetes were identified (incidence 1.6%). The best-fitting model indicated that among all modifiable risk factors included, waist circumference had the biggest direct effect on type 2 diabetes (standardized ß-coefficient 0.214), followed by HDL-cholesterol (standardized ß-coefficient - 0.134). Less TV watching and more physical activity were found to play an important role in improving clinical markers that were directly associated with type 2 diabetes. Education had the biggest positive effects on all lifestyle behaviors except for unhealthy sleep duration. Our analysis provides evidence to support that structural equation modeling enables a holistic assessment of the interplay of type 2 diabetes risk factors, which not only allows the estimation of their total effects but also prioritization of prevention targets. Regarding the current guideline for diabetes prevention, waist management in addition to BMI control (clinical level), as well as less TV watching in addition to more physical activity (behavioral level), may provide additional public health benefits. Better education would be the main societal goal for the prevention of type 2 diabetes.

Ultra-processed food and incident type 2 diabetes: studying the underlying consumption patterns to unravel the health effects of this heterogeneous food category in the prospective Lifelines cohort.

BACKGROUND: The overall consumption of ultra-processed food (UPF) has previously been associated with type 2 diabetes. However, due to the substantial heterogeneity of this food category, in terms of their nutritional composition and product type, it remains unclear whether previous results apply to all underlying consumption patterns of UPF. METHODS: Of 70,421 participants (35-70 years, 58.6% women) from the Lifelines cohort study, dietary intake was assessed with a food frequency questionnaire. UPF was identified according to the NOVA classification. Principal component analysis (PCA) was performed to derive UPF consumption patterns. The associations of UPF and adherence to UPF consumption patterns with incidence of type 2 diabetes were studied with logistic regression analyses adjusted for age, sex, diet quality, energy intake, alcohol intake, physical activity, TV watching time, smoking status, and educational level. RESULTS: During a median follow-up of 41 months, a 10% increment in UPF consumption was associated with a 25% higher risk of developing type 2 diabetes (1128 cases; OR 1.25 [95% CI 1.16, 1.34]). PCA revealed four habitual UPF consumption patterns. A pattern high in cold savory snacks (OR 1.16 [95% CI 1.09, 1.22]) and a pattern high in warm savory snacks (OR 1.15 [95% CI 1.08, 1.21]) were associated with an increased risk of incident type 2 diabetes; a pattern high in traditional Dutch cuisine was not associated with type 2 diabetes incidence (OR 1.05 [95% CI 0.97, 1.14]), while a pattern high in sweet snacks and pastries was inversely associated with type 2 diabetes incidence (OR 0.82 [95% CI 0.76, 0.89]). CONCLUSIONS: The heterogeneity of UPF as a general food category is reflected by the discrepancy in associations between four distinct UPF consumption patterns and incident type 2 diabetes. For better public health prevention, research is encouraged to further clarify how different UPF consumption patterns are related to type 2 diabetes.

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.

Blood lipids-related dietary patterns derived from reduced rank regression are associated with incident type 2 diabetes.

BACKGROUND & AIMS: Blood lipids play a critical role in the pathogenesis of type 2 diabetes, and they are closely related to dietary factors. However, the associations between blood lipids-related dietary patterns and risk of type 2 diabetes are controversial and not fully clear. In this study, we aimed to derive dietary patterns that explained variation in blood lipids and to investigate their associations with incident type 2 diabetes. METHODS: The analysis was based on 39,000 women and 25,777 men participating in the Lifelines cohort study (aged 18-65 years, mean 43.2 years for women and 43.5 years for men). Dietary intake was measured using a 110-item semi-quantitative food frequency questionnaire. Reduced rank regression was used to derive dietary patterns with blood lipids (HDL-cholesterol, LDL-cholesterol, triglycerides, total cholesterol, and total cholesterol:HDL-cholesterol ratio) as response variables for women and men separately. The first dietary pattern identified for each sex was selected because they explained the largest variance in blood lipids. The associations between the identified dietary patterns and incident type 2 diabetes were subsequently investigated using multivariate logistic regression models. All analyses were performed separately for women and men. RESULTS: During an average follow-up of 43 months, 479 new cases (incidence 0.74%) of type 2 diabetes were identified. Using reduced rank regression, we identified two sex-specific blood lipids-associated dietary patterns characterized by high intake of sugary beverages, added sugar, and low intake of vegetables, fruits, tea, and nuts/seeds. These two sex-specific dietary patterns were similar in food groups but differed in factor loadings. High dietary pattern scores were associated with increased risk of type 2 diabetes after adjustment for age, total energy intake, body mass index, waist-hip ratio, and blood pressure (ORs for the fifth quintile [Q5] using the first quintile [Q1] as reference, 1.87 [95% CI 1.23, 2.83] for women [P-trend < 0.001], and 1.72 [95% CI 1.11, 2.66] for men [P-trend = 0.018]). The associations were attenuated but remained significant after further adjustment for lifestyle and socio-economic factors. CONCLUSIONS: Dietary patterns associated with adverse blood lipids are associated with incidence of type 2 diabetes. The present study provides new insights in optimizing blood lipids for the prevention of type 2 diabetes through dietary approaches.

Association between socioeconomic status and self-reported, tested and diagnosed COVID-19 status during the first wave in the Northern Netherlands: a general population-based cohort from 49 474 adults.

OBJECTIVES: Studies in clinical settings showed a potential relationship between socioeconomic status (SES) and lifestyle factors with COVID-19, but it is still unknown whether this holds in the general population. In this study, we investigated the associations of SES with self-reported, tested and diagnosed COVID-19 status in the general population. DESIGN, SETTING, PARTICIPANTS AND OUTCOME MEASURES: Participants were 49 474 men and women (46±12 years) residing in the Northern Netherlands from the Lifelines cohort study. SES indicators and lifestyle factors (i.e., smoking status, physical activity, alcohol intake, diet quality, sleep time and TV watching time) were assessed by questionnaire from the Lifelines Biobank. Self-reported, tested and diagnosed COVID-19 status was obtained from the Lifelines COVID-19 questionnaire. RESULTS: There were 4711 participants who self-reported having had a COVID-19 infection, 2883 participants tested for COVID-19, and 123 positive cases were diagnosed in this study population. After adjustment for age, sex, lifestyle factors, body mass index and ethnicity, we found that participants with low education or low income were less likely to self-report a COVID-19 infection (OR [95% CI]: low education 0.78 [0.71 to 0.86]; low income 0.86 [0.79 to 0.93]) and be tested for COVID-19 (OR [95% CI]: low education 0.58 [0.52 to 0.66]; low income 0.86 [0.78 to 0.95]) compared with high education or high income groups, respectively. CONCLUSION: Our findings suggest that the low SES group was the most vulnerable population to self-reported and tested COVID-19 status in the general population.