Statistical analysis
Continuous variables were expressed as mean ± standard deviation (SD) or
median (P25, P75), and categorical variables were expressed as
percentages. We compared the distribution of participants with different
demographic characteristics by chronotypes (morning chronotype, neutral
chronotype, and evening chronotype) using t-tests and analysis of
variance (ANOVA) for continuous variables or Chi-square tests and
Fisher’s exact test for categorical variables. Binary logistic
regression models were used to examine the relationship between
chronotype and depressive symptoms during infertility treatment.
Hypothesis testing was performed to ensure that the assumptions of the
regression model were met. Since the missing values are few, we handle
it by deleting the rows.
We used the evening chronotype as the reference group in the binary
logistic regression models to assess the odds ratios (ORs) and 95%
confidence intervals (CIs) for chronotype on the depressive status and
adjusted for possible confounding variables in the final model,
including age, sex, annual income, education, passive smoking, physical
activity, living children, infertility treatment time, cause of
infertility, frequency of insomnia, nocturnal wake frequency, daytime
napping, social jetlag, and nighttime sleep duration. Trend tests were
performed using the median of the different categories of chronotypes
scores as a continuous variable. Restrictive cubic splines with five
knots were conducted to characterize the dose-response curve between
sleep and depressive symptoms. We also tested the interaction effect and
estimated the relationship between chronotype and odds of depressive
symptoms by stratification of the covariates above. A sensitivity
analysis was applied to test the robustness of the results. As well, we
utilized the Actor- Partner Interdependence Mode (APIM) approach to
explore the partner effect of own chronotype on the spouse’s depressive
symptoms, as recommended by Kenny et al 36. In our
study, the actor effect refers to the influence of a person’s chronotype
on his/her own depressive symptoms, and the partner effect refers to the
influence of a person’s chronotype on his/her spouse’s depressive
symptoms. The APIM framework for a husband-wife dyad is also described
in Figure S3 .
All the above statistical analyses were carried out using R software
version 4.1.0 (University of Auckland, Auckland, New Zealand), SPSS
version 23.0 (SPSS, Chicago, IL, USA), and Mplus software (version 8.3).
In current study, all statistical tests were double-tailed and the level
of significance was p -value <0.05 which was considered
statistically significant.