Self-Reported Health as Predictor of Allostatic Load and All-Cause Mortality: Findings From the Lolland-Falster Health Study

Objectives: The aim was to determine the association between self-reported health (SRH), allostatic load (AL) and mortality.Methods: Data derived from the Lolland-Falster Health Study undertaken in Denmark from 2016–2020 (n = 14,104). Median follow-up time for death was 4.6 years where 456 participants died. SRH was assessed with a single question and AL by an index of ten biomarkers. Multinomial regression analysis were used to examine the association between SRH and AL, and Cox regression to explore the association between SRH, AL and mortality.Results: The risk of high AL increased by decreasing level of SRH. The ratio of relative risk (RRR) of having medium vs. low AL was 1.58 (1.11–2.23) in women reporting poor/very poor SRH as compared with very good SRH. For men it was 1.84 (1.20–2.81). For high vs. low AL, the RRR was 2.43 (1.66–3.56) in women and 2.96 (1.87–4.70) in men. The hazard ratio (HR) for all-cause mortality increased by decreasing SRH. For poor/very poor vs. very good SRH, the HR was 6.31 (2.84–13.99) in women and 3.92 (2.12–7.25) in men.Conclusion: Single-item SRH was able to predict risk of high AL and all-cause mortality

Predicting diabetes-related conditions in need of intervention: Lolland-Falster Health Study, Denmark

In the Danish population, about one-in-ten adults have prediabetes, undiagnosed, poorly or potentially sub-regulated diabetes, for short DMRC. It is important to offer these citizens relevant healthcare intervention. We therefore built a model for prediction of prevalent DMRC.Data were derived from the Lolland-Falster Health Study undertaken in a rural-provincial area of Denmark with disadvantaged health. We included variables from public registers (age, sex, age, citizenship, marital status, socioeconomic status, residency status); from self-administered questionnaires (smoking status, alcohol use, education, self-rated health, dietary habits, physical activity); and from clinical examinations (body mass index (BMI), pulse rate, blood pressure, waist-to-hip ratio). Data were divided into training/testing datasets for development and testing of the prediction model.The study included 15,801 adults; of whom 1,575 with DMRC. Statistically significant variables in the final model included age, self-rated health, smoking status, BMI, waist-to-hip ratio, and pulse rate. In the testing dataset this model had an area under the curve (AUC) = 0.77 and a sensitivity of 50% corresponding to a specificity of 84%.In a health disadvantaged Danish population, presence of prediabetes, undiagnosed, or poorly or potentially sub-regulated diabetes could be predicted from age, self-rated health, smoking status, BMI, waist-to-hip ratio, and pulse rate. Age is known from the Danish personal identification number, self-rated health and smoking status can be obtained from simple questions, and BMI, waist-to-hip ratio, and pulse rate can be measured by any person in health care and potentially by the person him/her-self. Our model might therefore be useful as a screening tool

Allostatic load as predictor of mortality: a cohort study from Lolland-Falster, Denmark

OBJECTIVES: The purposes of the present study were to determine the association between (1) 10 individual biomarkers and all-cause mortality; and between (2) allostatic load (AL), across three physiological systems (cardiovascular, inflammatory, metabolic) and all-cause mortality. DESIGN: Prospective cohort study. SETTING: We used data from the Lolland-Falster Health Study undertaken in Denmark in 2016–2020 and used data on systolic blood pressure (SBP) and diastolic blood pressure (DBP), pulse rate (PR), waist–hip ratio (WHR) and levels of low-density lipoprotein cholesterol (LDL-c), high-density lipoprotein cholesterol (HDL-c), triglycerides, glycated haemoglobin A1c (HbA1c), C-reactive protein (CRP) and serum albumin. All biomarkers were divided into quartiles with high-risk values defined as those in the highest (PR, WHR, triglycerides, HbA1c, CRP) or lowest (HDL-c, albumin) quartile, or a combination hereof (LDL-c, SBP, DBP). The 10 biomarkers were combined into a summary measure of AL index. Participants were followed-up for death for an average of 2.6 years. PARTICIPANTS: We examined a total of 13 725 individuals aged 18+ years. PRIMARY OUTCOME MEASURE: Cox proportional hazard regression (HR) analysis were performed to examine the association between AL index and mortality in men and women. RESULTS: All-cause mortality increased with increasing AL index. With low AL index as reference, the HR was 1.33 (95% CI: 0.89 to 1.98) for mid AL, and HR 2.37 (95% CI: 1.58 to 3.54) for high AL. CONCLUSIONS: Elevated physiological burden measured by mid and high AL index was associated with a steeper increase of mortality than individual biomarkers

Correlation between allostatic load index and cumulative mortality: a register-based study of Danish municipalities

Objectives The aim of this study was to examine population-based allostatic load (AL) indices as an indicator of community health across 14 municipalities in Denmark.Design Register-based study.Setting Data derived from: the Lolland-Falster Health Study, the Copenhagen General Population Study and the Danish General Suburban Population Study. Nine biomarkers (systolic blood pressure, diastolic blood pressure, pulse rate, total serum cholesterol, high-density lipoprotein cholesterol, waist-to-hip ratio, triglycerides, C-reactive protein and serum albumin) were divided into high-risk and low-risk values based on clinically accepted criteria, and the AL index was defined as the average between the nine values. All-cause mortality data were obtained from Statistics Denmark.Participants We examined a total of 106 808 individuals aged 40–79 years.Primary outcome measure Linear regression models were performed to investigate the association between mean AL index and cumulative mortality risk.Results Mean AL index was higher in men (range 2.3–3.3) than in women (range 1.7–2.6). We found AL index to be strongly correlated with the cumulative mortality rate, correlation coefficient of 0.82. A unit increase in mean AL index corresponded to an increase in the cumulative mortality rate of 19% (95% CI 13% to 25%) for men, and 16% (95% CI 8% to 23%) for women but this difference was not statistically significant. The overall mean increase in cumulative mortality rate for both men and women was 17% (95% CI 14% to 20%).Conclusions Our findings indicate the population-based AL index to be a strong indicator of community health, and suggest identification of targets for reducing AL

Detailed descriptions of physical activity patterns among individuals with prediabetes and diabetes: The Lolland-Falster Health Study

Despite the importance of physical activity for type 2 diabetes, it is largely unknown to what extent physical activity patterns vary among individuals with prediabetes and diabetes. Recent developments of technological wearable devices provide new possibilities to describe detailed patterns of physical activity, physical postures, sleep characteristics, and other physiological factors over long time periods. The second-by-second continuous assessment offer many opportunities to advance research also among individuals with diabetes and other chronic conditions. No previous large-scale studies have provided a detailed description of objectively assessed habitual physical activity patterns among individuals with prediabetes and diabetes. Availability of such information would be an important resource for planning future treatment courses taking individual characteristics, needs, and preferences into account when designing a physical activity intervention. Therefore, the overall aim of this study is to describe physical activity behaviors and patterns among individuals with prediabetes and diabetes and compare these patterns with individuals with no known diabetes

Detailed descriptions of physical activity patterns among individuals with diabetes and prediabetes: the Lolland-Falster Health Study

Introduction This study aimed to describe objectively measured physical activity patterns, including daily activity according to day type (weekdays and weekend days) and the four seasons, frequency, distribution, and timing of engagement in activity during the day in individuals with diabetes and prediabetes and compared with individuals with no diabetes.Research design and methods This cross-sectional study included data from the Danish household-based, mixed rural-provincial population study, The Lolland-Falster Health Study from 2016 to 2020. Participants were categorized into diabetes, prediabetes, and no diabetes based on their glycated hemoglobin level and self-reported use of diabetes medication. Outcome was physical activity in terms of intensity (time spent in sedentary, light, moderate, vigorous, and moderate to vigorous physical activity (MVPA) intensities), adherence to recommendations, frequency and distribution of highly inactive days (<5 min MVPA/day), and timing of engagement in activity assessed with a lower-back worn accelerometer.Results Among 3157 participants, 181 (5.7 %) had diabetes and 568 (18.0 %) had prediabetes. Of participants with diabetes, 63.2% did not adhere to the WHO recommendations of weekly MVPA, while numbers of participants with prediabetes and participants with no diabetes were 59.5% and 49.6%, respectively. Around a third of participants with diabetes were highly inactive daily (<5 min MVPA/day) and had >2 consecutive days of inactivity during a 7-days period. Mean time spent physically active at any intensity (light, moderate, and vigorous) during a day was lower among participants with diabetes compared with participants with no diabetes and particularly from 12:00 to 15:00 (mean difference of −6.3 min MVPA (95% CI −10.2 to −2.4)). Following adjustments, significant differences in physical activity persisted between diabetes versus no diabetes, but between participants with prediabetes versus no diabetes, results were non-significant after adjusting for body mass index.Conclusions Inactivity was highly prevalent among individuals with diabetes and prediabetes, and distinct daily activity patterns surfaced when comparing these groups with those having no diabetes. This highlights a need to optimize current diabetes treatment and prevention to accommodate the large differences in activity engagement