Exploring the variation in associations between socioeconomic indicators and non-communicable diseases in the Tromsø Study: an algorithmic approach.

AIMS: We contribute to the methodological literature on the assessment of health inequalities by applying an algorithmic approach to evaluate the capabilities of socioeconomic variables in predicting the prevalence of non-communicable diseases in a Norwegian health survey. METHODS: We use data from the seventh survey of the population based Tromsø Study (2015-2016), including 11,074 women and 10,009 men aged 40 years and above. We apply the random forest algorithm to predict four non-communicable disease outcomes (heart attack, cancer, diabetes and stroke) based on information on a number of social root causes and health behaviours. We evaluate our results using the classification error, the mean decrease in accuracy, partial dependence statistics. RESULTS: Results suggest that education, household income and occupation to a variable extent contribute to predicting non-communicable disease outcomes. Prediction misclassification ranges between 25.1% and 35.4% depending on the non-communicable diseases under study. Partial dependences reveal mostly expected health gradients, with some examples of complex functional relationships. Out-of-sample model validation shows that predictions translate to new data input. CONCLUSIONS: Algorithmic modelling can provide additional empirical detail and metrics for evaluating heterogeneous inequalities in morbidity. The extent to which education, income and occupation contribute to predicting binary non-communicable disease outcomes depends on both non-communicable diseases and socioeconomic indicator. Partial dependences reveal that social gradients in non-communicable disease outcomes vary in shape between combinations of non-communicable disease outcome and socioeconomic status indicator. Misclassification rates highlight the extent of variation within socioeconomic groups, suggesting that future studies may improve predictive accuracy by exploring further subpopulation heterogeneity.

Trends in known and undiagnosed diabetes, HbA1c levels, cardiometabolic risk factors and diabetes treatment target achievement in repeated cross-sectional surveys: the population-based Tromsø Study 1994-2016.

OBJECTIVES: The aim of this study was to investigate time trends in known and undiagnosed diabetes, glycated haemoglobin (HbA1c) levels and other cardiometabolic risk factors in the general population as well as treatment target achievement among those with diabetes. DESIGN AND SETTING: Repeated cross-sectional surveys in the population-based Tromsø Study. METHODS: We used age-adjusted generalised estimating equation models to study trends in self-reported and undiagnosed (HbA1c ≥6.5%) diabetes, cardiometabolic risk factors and the metabolic syndrome in 27 281 women and men aged 40-84 years examined in up to four surveys of the Tromsø Study between 1994 and 2016. Further, we analysed trends in diabetes treatment target achievement. RESULTS: During 1994-2016, diabetes prevalence increased in women (2.3% to 4.6%) and men (2.4% to 5.8%) and in all age groups, while the proportion of undiagnosed diabetes in women (32% to 17%) and men (37% to 24%) decreased. Blood pressure and total cholesterol decreased, while waist circumference increased in participants with and without diabetes, leading to a relatively stable prevalence of the metabolic syndrome throughout the study period. There was a marginal increase in HbA1c levels among participants without diabetes. Only half of those with diabetes achieved the treatment target of HbA1c ≤7.0%. CONCLUSION: In the last two decades, diabetes prevalence increased, while the proportion of undiagnosed diabetes declined. The prevalence of the metabolic syndrome remained stable throughout, driven by opposing trends with an increase in obesity and a decrease in other cardiometabolic risk factors. HbA1c treatment target achievement did not improve.

Frailty phenotype and its association with all-cause mortality in community-dwelling Norwegian women and men aged 70 years and older: The Tromsø Study 2001-2016.

AIM: There is a lack of studies on the prevalence of frailty, and the association between frailty and mortality in a Norwegian general population. Findings regarding sex differences in the association between frailty and mortality have been inconsistent. The aim of the present study was to investigate the association between the frailty phenotype and all-cause mortality in men and women in a Norwegian cohort study. METHODS: We followed 712 participants (52% women) aged ≥70 years participating in the population-based Tromsø 5 Study in 2001-2002 for all-cause mortality up to 2016. The frailty status at baseline was defined by a modified version of Fried's frailty criteria. Cox regression models were used to analyze the association between frailty and mortality with adjustment for age, sex, disability, comorbidity, smoking status and years of education. RESULTS: In total, 3.8% (n = 27) of participants were frail (women 4.4%, men 3.2%) and 38.1% (n = 271) were pre-frail (women 45.8%, men 29.9%). During follow-up (mean 10.1 years), 501 (70%) participants died. We found an increased risk of mortality for frail older adults (multivariable-adjusted HR 4.16, 95% CI 2.40-7.22) compared with non-frail older adults. In sex-stratified analysis, the adjusted HR was 7.09 (95% CI 3.03-16.58) for frail men and 2.93 (95% CI 1.38-6.22) for frail women. Results for pre-frailty showed an overall weaker association with mortality. CONCLUSIONS: While frailty was more prevalent in women than in men, the findings suggest that the association between frailty and mortality is stronger in men than in women. Geriatr Gerontol Int 2018; 18: 1200-1205.