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.

ObjectivesStudies 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 measuresParticipants 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.ResultsThere 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.ConclusionOur findings suggest that the low SES group was the most vulnerable population to self-reported and tested COVID-19 status in the general population.

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.

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.