Title: Trajectories of depressive symptoms and risk of chronic liver disease: Evidence from
CHARLS
Version: 1 Date: 26 Feb 2025
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-The exclusion of participants with psychiatric disorders (4798) and pre-existing CLD (1050)
in the initial waves is understandable to avoid confounding. However, it would be useful to
elaborate on whether this exclusion might introduce any bias into the results. For example,
excluding those with psychiatric disorders may miss individuals with comorbid depression and
liver disease, which could affect the generalizability of the findings.
-While the study mentions that CLD is diagnosed by a physician and self-reported by
participants, the method of diagnosis (e.g., clinical examination, biomarkers, medical records)
could be better described. Without more details on how CLD was diagnosed, the accuracy of
the CLD classification may be questioned. It would be ideal to specify whether the diagnosis
was confirmed by a medical professional at each wave or if self-reported data alone were used.
-The exclusion of participants with incomplete data (e.g., missing CES-D scores or CLD
data) raises the question of whether missing data might introduce bias. It would be helpful to
clarify the approach used for handling missing data, such as whether imputation methods were
employed or if a complete case analysis was conducted. This would address concerns about the
representativeness of the study sample.
-While LCGM and GMM are excellent statistical approaches to analyzing longitudinal
depressive trajectories, it might be beneficial to explain why these specific methods were chosen
over other possible techniques, such as latent trajectory models or other growth mixture models.
Additionally, more details on how the model fit was assessed (e.g., fit indices, cross-validation)
would help readers understand the robustness of the model selection process.
-The study excludes cancers from the CLD category, but it would be valuable to explain why
this exclusion was made. It would also be useful to specify how the diagnosis of CLD was
handled in the presence of comorbid conditions like cancer or other liver-related diseases that
might complicate the analysis.
-The authors acknowledge that they did not explore the bidirectional relationship between
depressive symptoms and CLD. Depression could both be a cause and a consequence of CLD,
and this aspect should be addressed to fully understand the dynamics of the relationship. The
lack of consideration of this bi-directionality is a significant limitation.
-While the study adjusts for confounders, there could be other unmeasured variables (e.g.,
genetic factors, access to healthcare, or socioeconomic status) that might influence both
depressive symptoms and CLD risk. Addressing these potential confounders would provide a
clearer understanding of the relationship between the two.
Title: Trajectories of depressive symptoms and risk of chronic liver disease: Evidence from
CHARLS
Version: 1 Date: 26 Feb 2025
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-The exclusion of participants with psychiatric disorders (4798) and pre-existing CLD (1050)
in the initial waves is understandable to avoid confounding. However, it would be useful to
elaborate on whether this exclusion might introduce any bias into the results. For example,
excluding those with psychiatric disorders may miss individuals with comorbid depression and
liver disease, which could affect the generalizability of the findings.
-While the study mentions that CLD is diagnosed by a physician and self-reported by
participants, the method of diagnosis (e.g., clinical examination, biomarkers, medical records)
could be better described. Without more details on how CLD was diagnosed, the accuracy of
the CLD classification may be questioned. It would be ideal to specify whether the diagnosis
was confirmed by a medical professional at each wave or if self-reported data alone were used.
-The exclusion of participants with incomplete data (e.g., missing CES-D scores or CLD
data) raises the question of whether missing data might introduce bias. It would be helpful to
clarify the approach used for handling missing data, such as whether imputation methods were
employed or if a complete case analysis was conducted. This would address concerns about the
representativeness of the study sample.
-While LCGM and GMM are excellent statistical approaches to analyzing longitudinal
depressive trajectories, it might be beneficial to explain why these specific methods were chosen
over other possible techniques, such as latent trajectory models or other growth mixture models.
Additionally, more details on how the model fit was assessed (e.g., fit indices, cross-validation)
would help readers understand the robustness of the model selection process.
-The study excludes cancers from the CLD category, but it would be valuable to explain why
this exclusion was made. It would also be useful to specify how the diagnosis of CLD was
handled in the presence of comorbid conditions like cancer or other liver-related diseases that
might complicate the analysis.
-The authors acknowledge that they did not explore the bidirectional relationship between
depressive symptoms and CLD. Depression could both be a cause and a consequence of CLD,
and this aspect should be addressed to fully understand the dynamics of the relationship. The
lack of consideration of this bi-directionality is a significant limitation.
-While the study adjusts for confounders, there could be other unmeasured variables (e.g.,
genetic factors, access to healthcare, or socioeconomic status) that might influence both
depressive symptoms and CLD risk. Addressing these potential confounders would provide a
clearer understanding of the relationship between the two.
Please review this paper.
user
Title: Trajectories of depressive symptoms and risk of chronic liver disease: Evidence from
CHARLS
Version: 1 Date: 26 Feb 2025
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-The exclusion of participants with psychiatric disorders (4798) and pre-existing CLD (1050)
in the initial waves is understandable to avoid confounding. However, it would be useful to
elaborate on whether this exclusion might introduce any bias into the results. For example,
excluding those with psychiatric disorders may miss individuals with comorbid depression and
liver disease, which could affect the generalizability of the findings.
-While the study mentions that CLD is diagnosed by a physician and self-reported by
participants, the method of diagnosis (e.g., clinical examination, biomarkers, medical records)
could be better described. Without more details on how CLD was diagnosed, the accuracy of
the CLD classification may be questioned. It would be ideal to specify whether the diagnosis
was confirmed by a medical professional at each wave or if self-reported data alone were used.
-The exclusion of participants with incomplete data (e.g., missing CES-D scores or CLD
data) raises the question of whether missing data might introduce bias. It would be helpful to
clarify the approach used for handling missing data, such as whether imputation methods were
employed or if a complete case analysis was conducted. This would address concerns about the
representativeness of the study sample.
-While LCGM and GMM are excellent statistical approaches to analyzing longitudinal
depressive trajectories, it might be beneficial to explain why these specific methods were chosen
over other possible techniques, such as latent trajectory models or other growth mixture models.
Additionally, more details on how the model fit was assessed (e.g., fit indices, cross-validation)
would help readers understand the robustness of the model selection process.
-The study excludes cancers from the CLD category, but it would be valuable to explain why
this exclusion was made. It would also be useful to specify how the diagnosis of CLD was
handled in the presence of comorbid conditions like cancer or other liver-related diseases that
might complicate the analysis.
-The authors acknowledge that they did not explore the bidirectional relationship between
depressive symptoms and CLD. Depression could both be a cause and a consequence of CLD,
and this aspect should be addressed to fully understand the dynamics of the relationship. The
lack of consideration of this bi-directionality is a significant limitation.
-While the study adjusts for confounders, there could be other unmeasured variables (e.g.,
genetic factors, access to healthcare, or socioeconomic status) that might influence both
depressive symptoms and CLD risk. Addressing these potential confounders would provide a
clearer understanding of the relationship between the two.
assistant