We examined associations between family status (living with a spouse or partner and number of children) and lifetime depression.
We used data from the UK Biobank, a large prospective study of middle-aged and older adults. Lifetime depression was assessed as part of a follow-up mental health questionnaire. Logistic regression was used to estimate associations between family status and depression. We included extensive adjustment for social, demographic and other potential confounders, including depression polygenic risk scores.
52,078 participants (mean age = 63.6, SD = 7.6; 52% female) were included in our analyses. Living with a spouse or partner was associated with substantially lower odds of lifetime depression (OR = 0.67, 95% CI 0.62-0.74). Compared to individuals without children, we found higher odds of lifetime depression for parents of one child (OR = 1.17, 95% CI 1.07-1.27) and parents of three (OR = 1.11, 95% CI 1.03-1.20) or four or more children (OR = 1.27, 95% CI 1.14-1.42). Amongst those not cohabiting, having any number of children was associated with higher odds of lifetime depression. Our results were consistent across age groups, the sexes, neighbourhood deprivation and genetic risk for depression. Exploratory Mendelian randomisation analyses suggested a causal effect of number of children on lifetime depression.
Limitations Our data did not allow distinguishing between non-marital and marital cohabitation. Results may not generalise to all ages or populations.
Living with a spouse or partner was strongly associated with reduced odds of depression. Having one or three or more children was associated with increased odds of depression, especially in individuals not living with a spouse or partner.
Exploring predictors of healthy ageing in UK Biobank
Substantial improvements in human health and significant increases in life expectancy are amongst the main achievements of civilization in the 20th and 21st centuries. However, many people spend a significant part of their lives suffering from age-related illness and experience decreased levels of normal functioning which is often associated with lower quality of life. To increase our understanding of the processes and mechanisms that are associated with good health outcomes in old age, this research will investigate some of the key environmental risk factors, lifestyle and the biology underlying healthy ageing. Moreover, we will examine ageing trajectories in individuals diagnosed with common mental illnesses such as depression and in chronic pain as previous research has shown that individuals with these diagnoses have higher rates of morbidity and mortality. Facing up to the global challenges of an ageing population is one of today's most important undertakings and the UK Biobank cohort provides an unprecedented data resource to investigate how people age. We will incorporate data from the baseline assessment and follow-up data that are available through record linkage and repeat assessments. All available data relating to the variables of interest for the full cohort will be analysed using appropriate statistical and machine learning methods. We anticipate a project duration of 36 months. The findings of our research will inform public health policy aimed at promoting health in later life.
|Lead investigator:||Julian Mutz|
|Lead institution:||King's College London|