Trajectories of a set of ten functional somatic symptoms from adolescence to middle age

Abstract

Background: Functional somatic symptoms (FSS), or symptoms without a clear medical explanation are a considerable challenge for health care systems. There is no general consensus as to which symptoms should be regarded functional. Few longitudinal studies on the development of FSS exist and these have mainly been based on the assumption that the factorial structure of a FSS scores variable remains invariant over time. When the analysis covers longer periods of the life course, this may be challenged. The aim of our study was to investigate how ten functional somatic symptoms (FSS) evolve when individuals are ageing. Methods: The data of the Northern Swedish Cohort (n = 1001) from questionnaire surveys at ages 16, 18, 21, 30 and 42, were analysed. Participation rates remained very high over the five surveys. The list of symptoms included backache, breathlessness, dizziness, fatigue, headache or migraine, nausea, overstrain, palpitations, sleeplessness and stomach ache. We used multivariate trajectory analysis (TA) with logistic broken-stick regression models to describe sub-groups in the data. In multivariate TA the joint development of the set of item variables can be investigated. There is no need to construct a special FSS summary score variable. Results: Four well separated trajectories were identified. In two groups, healing symptoms (25.4% of the sample) and low symptom load (32.2% of the sample), the symptom level stayed relatively low in adulthood. In the third group of high symptom load (17.2%) the probability of having symptoms was high for all FSS variables. In the fourth group of increasing symptoms (25.3%) the level of symptoms was first intermediate, but increased markedly with age. Conclusions: Instead of a single FSS score we were able to assign each individual to one of four trajectories described jointly by 10 separate symptoms. The profile of development, but not the probability level, was rather similar over the symptoms within the trajectories, with few exceptions. The results provide better understanding of the longitudinal development of the symptoms from the adolescence to the middle age.

Risk factors in adolescence as predictors of trajectories of somatic symptoms over 27 years

“…In our previous study, we identified four trajectories of somatic symptoms from the age 16–43 (‘constantly low’, ‘increasing’, ‘decreasing’ and ‘constantly high’ symptom load). 20 In accordance with previous studies, the prevalence of symptoms was higher for women in our studies compared to men, but the development of symptoms was similar among both genders. 20 It is unclear whether there are gender differences in the predictors of symptom trajectories.…”

“… 18 Membership to a long-term high symptoms trajectory group was associated with the children experiencing more stress and negative life events, parenting stress at baseline and the child’s previous health, such as depressive symptoms, but not overprotective parenting style compared to low or decreasing groups. 16–18 Our own two previous studies on somatic symptoms 19 , 20 have covered the life course up to middle age. These studies, however, concentrated on methodology (multiple response trajectory analysis), and did not investigate predictors or outcomes.…”

Age-Dependent Translocation of Gold Nanoparticles across the Air–Blood Barrier

“…Pairwise comparisons were performed as needed by Tukey’s test. Segmented regression , shows the lack of difference in the translocation between 5 nm versus 100 nm AuNPs in the developing lungs.…”

“…Pairwise comparisons were performed as needed by Tukey's test. Segmented regression 14,15 shows the lack of difference in the translocation between 5 nm versus 100 nm AuNPs in the developing lungs. (Figure 4b; Table S2 in the Supporting Information provides the numerical values of data plotted in Figure 4b).…”

“…Statistical significance was determined by ANOVA, and P values of 0.01 or 0.05 are indicated. Segmented regression 14,15 shows the lack of difference in translocation of 5 nm vs 100 nm AuNPs in the developing lungs.…”