Cohort Profile: Better Health in Late Life

Purpose

Humans are living longer and may develop multiple chronic diseases in later life. The Better Health in Late Life cohort study aims to improve our understanding of the risks and outcomes of multimorbidity in the Danish population.

Methods

A randomly-selected sample of Danish residents who were 50-65 years of age received a questionnaire and an invitation to participate in this study. Respondents completed an online survey between October 2021 and January 2022 which addressed topics that included self-assessed health, mental health, sleep, specific medical conditions, use of painkillers, diet, alcohol consumption, smoking, physical activity, and body composition. This information was linked to the Danish health and social registries (some established in 1943 and onwards) that maintain data on filled prescriptions, hospital records, socioeconomic status, and health care utilization.

Results

Responses were received from 115,431 of the 301,244 residents invited to participate (38%). We excluded respondents who answered none of the questions as well as those who provided no information on sex or indicated an age other than 50-65 years. Of the 114,283 eligible respondents, 54.8% were female, 30.3% were overweight, and 16.7% were obese. Most participants reported a weekly alcohol consumption of less than seven units and 13.3% were current smokers; 5.2% had a history of hospitalization for solid cancer, and 3.0%, 2.3%, 2.0%, and 0.9% reported chronic pulmonary disease, diabetes, stroke, and myocardial infarction, respectively. The most frequently filled prescriptions were for medications used to treat the nervous system and cardiovascular diseases (38.1% and 37.4%, respectively).

Birth weight, childhood body mass index, and risk of diverticular disease in adulthood

OBJECTIVE

Adult overweight is associated with increased risk of diverticular disease (DD). We investigated associations between birthweight and childhood body mass index (BMI) and DD.

METHODS

Cohort study of 346,586 persons born during 1930-1996 with records in the Copenhagen School Health Records Register. Data included birthweight, and height and weight from ages 7 through 13. We used Cox proportional hazard regression to examine associations between birthweight and BMI z-scores and DD registered in the Danish National Patient Registry. Due to non-proportionality, we followed participants from age 18-49 and from age 50.

RESULTS

During follow-up, 5459 (3.2%) women and 4429 (2.5%) men had DD. For low and high BMI in childhood, we observed a higher risk of DD before age 50. Among women with z-scores <0 at age 13, the hazard ratio (HR) was 1.16 [95% confidence interval (CI): 0.98-1.39] per one-point lower z-score. For z-scores ≥0 at age 13, the HR was 1.30 (95% CI: 1.11-1.51) per one-point higher z-score. Among men with z-scores <0 at age 13, the HR was 1.02 (95% CI: 0.85-1.22). For z-scores ≥0 at age 13, the HR was 1.54 (95% CI: 1.34-1.78). Z-scores ≥0 were not associated with DD after age 50. Among women only, birthweight was inversely associated with DD before age 50 [HR = 0.90 (95% CI: 0.83-0.99) per 500 g higher birthweight].

CONCLUSION

BMI z-scores below and above zero in childhood were associated with higher risk of DD before age 50. In addition, we observed lower risk of DD among women, the higher their birthweight.

Perceived stress and semen quality

BACKGROUND

Psychological stress is prevalent among reproductive-aged men. Assessment of semen quality for epidemiological studies is challenging as data collection is expensive and cumbersome, and studies evaluating the effect of perceived stress on semen quality are inconsistent.

OBJECTIVE

To examine the association between perceived stress and semen quality.

MATERIAL AND METHODS

We analyzed baseline data on 644 men (1,159 semen samples) from two prospective preconception cohort studies during 2015-2021: 592 in Pregnancy Study Online (PRESTO) and 52 in SnartForaeldre.dk (SF). At study entry, men aged ≥21 years (PRESTO) and ≥18 years (SF) trying to conceive without fertility treatment completed a questionnaire on reproductive and medical history, socio-demographics, lifestyle, and the 10-item version of the Perceived Stress Scale (PSS; interquartile range [IQR] of scores: 0-40). After enrollment (median weeks: 2.1, IQR: 1.3-3.7), men were invited to perform in-home semen testing, twice with 7-10 days between tests, using the Trak Male Fertility Testing System. Semen quality was characterized by semen volume, sperm concentration, and total sperm count. We fit generalized estimating equation linear regression models to estimate the percent difference in mean log-transformed semen parameters by four PSS groups (<10, 10-14, 15-19, ≥20), adjusting for potential confounders.

RESULTS

The median PSS score and IQR was 15 (10-19), and 136 men (21.1%) had a PSS score ≥20. Comparing men with PSS scores ≥20 with <10, the adjusted percent difference was -2.7 (95% CI: -9.8; 5.0) for semen volume, 6.8 (95% CI: -10.9; 28.1) for sperm concentration, and 4.3 (95% CI: -13.8; 26.2) for total sperm count.

CONCLUSION

Our findings indicate that perceived stress is not materially associated with semen volume, sperm concentration, or total sperm count.

Air pollution and fecundability: Results from a Danish preconception cohort study

BACKGROUND

Animal and epidemiologic studies indicate that air pollution may adversely affect fertility. Epidemiologic studies have been restricted largely to couples undergoing fertility treatment or have retrospectively ascertained time-to-pregnancy among pregnant women.

OBJECTIVES

We examined the association between residential ambient air pollution and fecundability, the per-cycle probability of conception, in a large preconception cohort of Danish pregnancy planners.

METHODS

During 2007-2018, we used the Internet to recruit and follow women who were trying to conceive without the use of fertility treatment. Participants completed an online baseline questionnaire eliciting socio-demographic characteristics, lifestyle factors, and medical and reproductive histories and follow-up questionnaires every 8 weeks to ascertain pregnancy status. We determined concentrations of ambient nitrogen oxides (NOx ), nitrogen dioxide (NO2 ), carbon monoxide (CO), ozone (O3 ), particulate matter <2.5 µm (PM2.5 ) and <10 µm (PM10 ), and sulphur dioxide (SO2 ) at each participant's residential address. We calculated average exposure during the year before baseline, during each menstrual cycle over follow-up and during the entire pregnancy attempt time. We used proportional probabilities regression models to estimate fecundability ratios (FRs) and 95% confidence intervals (CIs), adjusting for potential confounders and co-pollutants. The analysis was restricted to the 10,183 participants who were trying to conceive for <12 cycles at study entry whose addresses could be geocoded.

RESULTS

During 12 months of follow-up, 73% of participants conceived. Higher concentrations of PM2.5 and PM10 were associated with small reductions in fecundability. For example, the FRs for a one interquartile range (IQR) increase in PM2.5 (IQR = 3.2 µg/m3 ) and PM10 (IQR = 5.3 µg/m3 ) during each menstrual cycle were 0.93 (95% CI: 0.87, 0.99) and 0.91 (95% CI: 0.84, 0.99), respectively. Other air pollutants were not appreciably associated with fecundability.

CONCLUSIONS

In this preconception cohort study of Danish women, residential exposures to PM2.5 and PM10 were associated with reduced fecundability.

Food substitution models for nutritional epidemiology

The advantage of using specified substitution analysis in nutritional epidemiology has been clearly demonstrated in studies of macronutrient intake and disease risk. However, the method has not been widely applied in studies of food intake. The aim of this article is to describe and compare the interpretation and application of different food substitution models in epidemiologic studies on diet and disease development. Both theoretically and in the context of a specific example, we discuss methodologic issues to be considered, including modeling of food substitutions using diet at a single time point or at multiple time points (focusing on dietary changes), choice of substitution unit, adjustment for total energy intake, and adjustment for confounding. We argue that specified food substitution analyses can be used to identify optimal food composition of the diet and that these analyses are thus highly relevant to inform public health policy decision makers.

Body mass index trajectories preceding first report of poor self-rated health: A longitudinal case-control analysis of the English Longitudinal Study of Ageing

Background

Studies have consistently found that obesity is associated with poor self-rated health, but how body mass index (BMI) developed in the lead up to poor self-rated health is unknown.

Methods

We nested a longitudinal case-control study in the English Longitudinal Study of Ageing (1998–2015) to investigate BMI trajectories in the years preceding a first self-report of poor health. Participants rated their health at each data collection; every other collection included a BMI assessment by a nurse. Case status was defined as a first report of poor health during follow-up. Three age- and sex-matched controls were identified per case using density sampling. BMI trajectories were fitted to time backwards prior to first report of poor health using mixed-effects models. Age and sex were potential modifiers. We conducted subgroup analyses of those not reporting certain chronic diseases or smoking.

Results

We identified 732 cases and 2195 controls. Age, but not sex, modified the association between BMI and self-rated health. Participants reporting poor health at age 60 had a 1.5 kg/m² (95%CI: 0.8 to 2.1) higher BMI at the time of reporting than controls, and their BMI had previously increased markedly (1.3 kg/m² 95%CI: 0.9 to 1.8 over ten years). After age 75, cases no longer had higher BMI than controls, and their BMI had decreased sharply prior to reporting poor health (e.g. -2.0 kg/m² 95%CI: -2.6 to -1.5 per decade on average for those reporting poor health at age 90). Age was also an effect modifier among those without diabetes, however BMI trajectories were more similar among the middle-aged. The subgroup analysis of those without cardiovascular disease, cancer and chronic lung disease showed similar results to the main findings.

Conclusion

Development of BMI was associated with poor self-rated health; however, the nature of the association depended markedly on age.