The Interaction of Genetic Predisposition and Socioeconomic Position With Type 2 Diabetes Mellitus: Cross-Sectional and Longitudinal Analyses From the Lifelines Cohort and Biobank Study

The effect of extended participation windows on attendance at cervical cancer screening

Research has long since confirmed the benefits of regular cervical cancer screening (CCS) worldwide. However, some developed countries have low participation rates despite well-organized screening programs. Given that studies in Europe typically define participation in 12-month windows from an invitation, we evaluated both whether extending this defined time window could reveal the true participation rate and how sociodemographic determinants affect participation delays. This involved linking data from the Lifelines population-based cohort with CCS-related data from the Dutch Nationwide Pathology Databank and including data for 69 185 women eligible for screening in the Dutch CCS program between 2014 and 2018. We then estimated and compared the participation rates for 15- and 36-month time windows and categorized women by the primary screening window into timely participation (within 15 months) and delayed participation (within 15-36 months) groups, before performing multivariable logistic regression to evaluate the association between delayed participation and the sociodemographic determinants. Participation rates for the 15- and 36-month windows were 71.1% and 77.0%, respectively, with participation considered timely in 49 224 cases and delayed in 4047 cases. Delayed participation was associated with age 30-35 years (odds ratio [OR]: 2.88, 95 %CI: 2.67-3.11), higher education (OR: 1.50, 95 %CI: 1.35-1.67), the high-risk human papillomavirus test-based program (OR: 1.67, 95 %CI: 1.56-1.79), and pregnancy (OR: 4.61, 95 %CI: 3.88-5.48). These findings show that a 36-month window for monitoring attendance at CCS better reflects the actual participation rate by accommodating possible delayed uptake among younger, pregnant, and highly educated women.

Associations of Genetic Factors, Educational Attainment, and Their Interaction With Kidney Function Outcomes

Both genetic predisposition and low educational attainment (EA) are associated with higher risk of chronic kidney disease. We examined the interaction of EA and genetic risk in kidney function outcomes. We included 3,597 participants from the Prevention of Renal and Vascular End-Stage Disease Cohort Study, a longitudinal study in a community-based sample from Groningen, the Netherlands (median follow-up, 11 years; 1997–2012). Kidney function was approximated by obtaining estimated glomerular filtration rate (eGFR) from serum creatinine and cystatin C. Individual longitudinal linear eGFR trajectories were derived from linear mixed models. Genotype data on 63 single-nucleotide polymorphisms, with known associations with eGFR, were used to calculate an allele-weighted genetic score (WGS). EA was categorized into high, medium, and low. In ordinary least squares analysis, higher WGS and lower EA showed additive effects on reduced baseline eGFR; the interaction term was nonsignificant. In analysis of eGFR decline, the significant interaction term suggested amplification of genetic risk by low EA. Adjustment for known renal risk factors did not affect our results. This study presents the first evidence of gene-environment interaction between EA and a WGS for eGFR decline and provides population-level insights into the mechanisms underlying socioeconomic disparities in chronic kidney disease.

A Genetic Risk Score Improves the Prediction of Type 2 Diabetes Mellitus in Mexican Youths but Has Lower Predictive Utility Compared With Non-Genetic Factors

Background

Type 2 diabetes (T2D) is a multifactorial disease caused by a complex interplay between environmental risk factors and genetic predisposition. To date, a total of 10 single nucleotide polymorphism (SNPs) have been associated with pediatric-onset T2D in Mexicans, with a small individual effect size. A genetic risk score (GRS) that combines these SNPs could serve as a predictor of the risk for pediatric-onset T2D.

Objective

To assess the clinical utility of a GRS that combines 10 SNPs to improve risk prediction of pediatric-onset T2D in Mexicans.

Methods

This case-control study included 97 individuals with pediatric-onset T2D and 84 controls below 18 years old without T2D. Information regarding family history of T2D, demographics, perinatal risk factors, anthropometric measurements, biochemical variables, lifestyle, and fitness scores were then obtained. Moreover, 10 single nucleotide polymorphisms (SNPs) previously associated with pediatric-onset T2D in Mexicans were genotyped. The GRS was calculated by summing the 10 risk alleles. Pediatric-onset T2D risk variance was assessed using multivariable logistic regression models and the area under the receiver operating characteristic curve (AUC).

Results

The body mass index Z-score (Z-BMI) [odds ratio (OR) = 1.7; p = 0.009] and maternal history of T2D (OR = 7.1; p < 0.001) were found to be independently associated with pediatric-onset T2D. No association with other clinical risk factors was observed. The GRS also showed a significant association with pediatric-onset T2D (OR = 1.3 per risk allele; p = 0.006). The GRS, clinical risk factors, and GRS plus clinical risk factors had an AUC of 0.66 (95% CI 0.56-0.75), 0.72 (95% CI 0.62-0.81), and 0.78 (95% CI 0.70-0.87), respectively (p < 0.01).

Conclusion

The GRS based on 10 SNPs was associated with pediatric-onset T2D in Mexicans and improved its prediction with modest significance. However, clinical factors, such the Z-BMI and family history of T2D, continue to have the highest predictive utility in this population.

The influence of unhealthy behaviours on early exit from paid employment among workers with a chronic disease: A prospective study using the Lifelines cohort

OBJECTIVES

This study examined the risk of unhealthy behaviours and the additive effects of multiple unhealthy behaviours on exit from paid employment among workers with a chronic disease and investigated effect modification by gender and educational level.

METHODS

Data from the Lifelines cohort, collected between 2006 and 2013, were enriched with registry data from Statistics Netherlands with up to 11 years follow-up. Workers with a chronic disease were selected (n = 11,467). The influence of unhealthy behaviours (physical inactivity, smoking, unhealthy diet, high alcohol intake, and obesity) on exit from paid employment (unemployment, disability benefits, early retirement, and economic inactivity) was examined using competing risk models. To examine effect modification by gender and educational level, interaction terms were added.

RESULTS

Smoking and low fruit intake increased the risk to exit paid employment through unemployment and disability benefits. Low vegetable intake increased the risk of unemployment, obesity the risk of receiving disability benefits, and high alcohol intake the risk of early retirement. Physical inactivity was not associated with any exit from paid employment. Having multiple unhealthy behaviours increased the risk of both unemployment and of receiving disability. No consistent effect modification for gender or educational level was found.

CONCLUSIONS

Unhealthy behaviours increased the risk to exit paid employment through unemployment and disability benefits among workers with a chronic disease, and this risk increased when having multiple unhealthy behaviours. Health promotion to support workers with chronic diseases to make healthier choices may help to extend their working life.

Occupational distribution of metabolic syndrome prevalence and incidence differs by sex and is not explained by age and health behavior: results from 75 000 Dutch workers from 40 occupational groups

INTRODUCTION

This study examines the association between 40 occupational groups and prevalence and incidence of metabolic syndrome (MetS), separately for male and female workers, and whether age and health behaviors can explain the association.

RESEARCH DESIGN AND METHODS

Data from 74 857 Lifelines Cohort and Biobank Study participants were used to regress occupational group membership, coded by Statistics Netherlands, on the prevalence and incidence of MetS using logistic and Cox regression analyses. MetS diagnosis was based on physical examinations, blood analysis, and recorded medication use. Information on age, smoking status, physical activity, diet and alcohol consumption was acquired using questionnaires.

RESULTS

Baseline MetS prevalence was 17.5% for males and 10.6% for females. During a median 3.8 years of follow-up, MetS incidence was 7.8% for males and 13.2% for females. One occupational group was associated with an increased MetS risk in both sexes. Six additional occupational groups had an increased risk for MetS among men, four among women. Highest risks were found for male 'stationary plant and machine operators' (HR: 1.94; 95% CI 1.26 to 3.00) and female 'food preparation assistants' (HR: 1.80; 95% CI 1.01 to 3.22).

CONCLUSIONS

Findings suggest that occupational group matters for men and women in MetS development, and that differences in MetS prevalence across occupations are not merely a reflection of selection of metabolically unhealthy workers into specific occupations. The striking sex differences in the occupational distribution of MetS indicate that preventive measures should, with some exceptions, target men and women separately.

Validating the doubly weighted genetic risk score for the prediction of type 2 diabetes in the Lifelines and Estonian Biobank cohorts

As many cases of type 2 diabetes (T2D) are likely to remain undiagnosed, better tools for early detection of high‐risk individuals are needed to prevent or postpone the disease. We investigated the value of the doubly weighted genetic risk score (dwGRS) for the prediction of incident T2D in the Lifelines and Estonian Biobank (EstBB) cohorts. The dwGRS uses an additional weight for each single nucleotide polymorphism in the risk score, to correct for “Winner's curse” bias in the effect size estimates. The traditional (single‐weighted genetic risk score; swGRS) and dwGRS were calculated for participants in Lifelines (n = 12,018) and EstBB (n = 34,129). The dwGRS was found to have stronger association with incident T2D (hazard ratio [HR] = 1.26 [95% confidence interval: 1.10–1.43] and HR = 1.35 [1.28–1.42]) compared to the swGRS (HR = 1.21 [1.07–1.38] and HR = 1.25 [1.19–1.32]) in Lifelines and EstBB, respectively. Comparing the 5‐year predicted risks from the models with and without the dwGRS, the continuous net reclassification index was 0.140 (0.034–0.243; p = .009 Lifelines), and 0.257 (0.194–0.319; p < 2 × 10⁻¹⁶ EstBB). The dwGRS provided incremental value to the T2D prediction model with established phenotypic predictors. It clearly distinguished the risk groups for incident T2D in both biobanks thereby showing its clinical relevance.