Cervical cancer mortality in Norway according to screening attendance and age.

INTRODUCTION: The association between cervical cancer screening and reduction of cervical cancer has been dealt with in much research. However, little has been published on the association between screening and cervical cancer mortality. We assessed cervical cancer deaths according to screening history, histopathology, and age among women in, under, and above screening age. MATERIAL AND METHODS: In this nationwide, registry-based case-control study from Norway, we included 817 cervical cancer deaths in women diagnosed with cervical cancer in the period 1998-2009. We matched each case with 10 population-based controls free from cervical cancer, obtained by density-based sampling. Odds ratios (ORs) with 95% confidence intervals (CIs) for the association between screening attendance and cervical cancer mortality were estimated using conditional logistic regression models. RESULTS: Of all fatal cervical cancers, 35% were diagnosed among women over screening age and altogether, 83% were either in age groups not covered by the screening program or in non-attenders of screening age. The estimated risk reduction associated with a cytology test in the preceding 3.5 years was 80% in screening age 25-69 years (OR 0.20; 95% CI 0.16-0.24) with the largest reduction in squamous cell carcinomas (84%) but also a substantial estimated risk reduction of 65% for adenocarcinomas. The associated risk reduction was strongest in women aged 45-69 years, with ORs in the range 0.09-0.18, compared with ORs 0.42-1.35 in women aged 25-39 years. CONCLUSIONS: To reduce the mortality of cervical cancer, screening programs should focus on increasing adherence to the program, as half of all the fatal cases were in the non-attender group. Further assessments regarding the potential preventive impact of extending screening to women over the current screening age should be considered.

Intergenerational polygenic obesity risk throughout adolescence in a cross-sectional study design: The HUNT study, Norway.

OBJECTIVE: This study examined the relationship between parental obesity polygenic risk and children's BMI throughout adolescence. Additionally, from a smaller subsample, the objective was to assess whether parental polygenic risk score (PRS) may act as a proxy for offspring PRS in studies lacking offspring genetic data. METHODS: A total of 8,561 parent-offspring (age 13-19 years) trios from the Trøndelag Health Study (the HUNT Study) were included, of which, 1,286 adolescents had available genetic data. Weighted parental PRSs from 900 single-nucleotide polymorphisms robustly associated with adult BMI were constructed and applied in linear mixed-effects models. RESULTS: A positive association between parental PRS and offspring sex- and age-adjusted BMI (iso-BMI) throughout adolescence was identified. The estimated marginal effects per standard deviation increase in parental PRS were 0.26 (95% CI: 0.18-0.33), 0.36 (95% CI: 0.29-0.43), and 0.62 kg/m2 (95% CI: 0.51-0.72) for maternal, paternal, and combined parental PRS, respectively. In subsample analyses, the magnitude of association of the parental PRS versus offspring PRS with iso-BMI in adolescents was similar. CONCLUSIONS: Parental PRS was consistently associated with offspring iso-BMI throughout adolescence. Results from subsample analyses support the use of parental PRS of obesity as a proxy for adolescent PRS in the absence of offspring genetic data.

Body mass index and all cause mortality in HUNT and UK Biobank studies: linear and non-linear mendelian randomisation analyses.

OBJECTIVE: To investigate the shape of the causal relation between body mass index (BMI) and mortality. DESIGN: Linear and non-linear mendelian randomisation analyses. SETTING: Nord-Trøndelag Health (HUNT) Study (Norway) and UK Biobank (United Kingdom). PARTICIPANTS: Middle to early late aged participants of European descent: 56 150 from the HUNT Study and 366 385 from UK Biobank. MAIN OUTCOME MEASURES: All cause and cause specific (cardiovascular, cancer, and non-cardiovascular non-cancer) mortality. RESULTS: 12 015 and 10 344 participants died during a median of 18.5 and 7.0 years of follow-up in the HUNT Study and UK Biobank, respectively. Linear mendelian randomisation analyses indicated an overall positive association between genetically predicted BMI and the risk of all cause mortality. An increase of 1 unit in genetically predicted BMI led to a 5% (95% confidence interval 1% to 8%) higher risk of mortality in overweight participants (BMI 25.0-29.9) and a 9% (4% to 14%) higher risk of mortality in obese participants (BMI ≥30.0) but a 34% (16% to 48%) lower risk in underweight (BMI <18.5) and a 14% (-1% to 27%) lower risk in low normal weight participants (BMI 18.5-19.9). Non-linear mendelian randomisation indicated a J shaped relation between genetically predicted BMI and the risk of all cause mortality, with the lowest risk at a BMI of around 22-25 for the overall sample. Subgroup analyses by smoking status, however, suggested an always-increasing relation of BMI with mortality in never smokers and a J shaped relation in ever smokers. CONCLUSIONS: The previously observed J shaped relation between BMI and risk of all cause mortality appears to have a causal basis, but subgroup analyses by smoking status revealed that the BMI-mortality relation is likely comprised of at least two distinct curves, rather than one J shaped relation. An increased risk of mortality for being underweight was only evident in ever smokers.

Health and unemployment: 14 years of follow-up on job loss in the Norwegian HUNT Study.

BACKGROUND: Many studies have investigated how unemployment influences health, less attention has been paid to the reverse causal direction; how health may influence the risk of becoming unemployed. We prospectively investigated a wide range of health measures and subsequent risk of unemployment during 14 years of follow-up. METHODS: Self-reported health data from 36 249 participants in the Norwegian HUNT2 Study (1995-1997) was linked by a personal identification number to the National Insurance Database (1992-2008). Exact dates of unemployment were available. Cox's proportional hazard models were used to estimate hazard ratios (HR) for the association of unemployment with several health measures. Adjustment variables were age, gender, education, marital status, occupation, lifestyle and previous unemployment. RESULTS: Compared to reporting no conditions/symptoms, having ≥3 chronic somatic conditions (HR 1.78, 95% CI 1.46-2.17) or high symptom levels of anxiety and depression (HR 1.57, 95% CI 1.35-1.83) increased the risk of subsequent unemployment substantially. Poor self-rated health (HR 1.36, 95% CI 1.24-1.51), insomnia (HR 1.19, 95% CI 1.09-1.32), gastrointestinal symptoms (HR 1.17, 95% CI 1.08-1.26), high alcohol consumption (HR 1.17, 95% CI 0.95-1.44) and problematic use of alcohol measured by the CAGE questionnaire (HR 1.32, 95% CI 1.17-1.48) were also associated with increased risk of unemployment. CONCLUSION: People with poor mental and physical health are at increased risk of job loss. This contributes to poor health amongst the unemployed and highlights the need for policy focus on the health and welfare of out of work individuals, including support preparing them for re-employment.

Mortality and work disability in a cohort of Norwegian couples--the HUNT study.

BACKGROUND: Poor health is clustered in families, and partners might influence each other. We studied possible consequences of living with a spouse with poor health or unhealthy lifestyle on mortality and work disability. METHODS: In total, 18 943 couples from the HUNT2 Study (1995-97) were linked to national registries and followed until December 2007, identifying deaths and disability pension retirements. Couple's mean exposures were included together with the individual's deviation from the couple mean in discrete time multilevel logistic regression. RESULTS: There was weak evidence of associations between partner's health and risk of dying. Associations between couples slightly exceeded associations within couples for smoking [odds ratio (OR) within 1.57 (95% confidence interval (CI): 1.38-1.78); OR between 1.88 (95% CI: 1.70-2.08), P value for difference 0.027] and education [OR within 1.07 (95% CI: 0.99-1.15); OR between 1.17 (1.11-1.23), P value for difference 0.065]. Indicators of partner's health, such as self-rated health [OR within 3.17 (95% CI: 2.80-3.58); OR between 3.92 (95% CI: 3.50-4.40), P value for difference 0.014], insomnia [OR within 1.39 (95% CI: 1.18-1.64); OR between 2.11 (95% CI: 1.86-2.53), P value for difference <0.001] and symptoms of depression [OR within 1.45 (95% CI: 1.22-1.71); OR between 1.98 (95% CI: 1.69-2.31) P value for difference 0.009] were, however, associated with risk of work disability. Self-rated health and symptoms displayed stronger associations with work disability among partners than reported somatic diseases. CONCLUSIONS: This study did not indicate strong consequences of living with a spouse with poor health or unhealthy lifestyle on mortality. It did, however, indicate associations of partner's health with work disability.