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2. In the ethics statement in the Methods, you have specified that verbal consent was obtained. Please provide additional details regarding how this consent was documented and witnessed, and state whether this was approved by the IRB

3. Thank you for stating the following financial disclosure:

“This work was supported by a grant from the German Center for Diabetes Research (DZD) funded by the German Federal Ministry of Education and Research (grant number: HMGU2022Z5) and grants from the German Federal Ministry of Health within the framework of the National Diabetes Surveillance project at the Robert Koch Institute (grant numbers: 2522DIA700 and 2523DIA002). The survey GEDA 2022 was funded by the Robert Koch Institute and the Federal Ministry of Health in Germany.”

Please state what role the funders took in the study. If the funders had no role, please state: "The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript."

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4. We noted in your submission details that a portion of your manuscript may have been presented or published elsewhere. “Parts of the results have previously been presented in abstract form at two scientific conferences (a German-language abstract for a national joint public health conference in Dresden [1], and an English-language poster at the 17th European Public Health Conference [2]). These prior formats do not constitute formal publication, and the full manuscript is original and has not been published or submitted elsewhere.

1. Neuperdt L, Du Y, Nübel J, Hapke U, Walther L, Mensink GBM, et al. Assoziation des Typ-2-Diabetes-Risikos mit selbsteingeschätzter allgemeiner und psychischer Gesundheit bei Erwachsenen in Deutschland – Ergebnisse der Studie GEDA 2022 Gesundheit – gemeinsam Kooperationstagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (GMDS), Deutschen Gesellschaft für Sozialmedizin und Prävention (DGSMP), Deutschen Gesellschaft für Epidemiologie (DGEpi), Deutschen Gesellschaft für Medizinische Soziologie (DGMS) und der Deutschen Gesellschaft für Public Health (DGPH); Dresden, Germany German Medical Science GMS Publishing House; 2024. doi: 10.3205/24gmds625

2. Neuperdt L, Du Y, Nübel J, Hapke U, Walther L, Mensink GBM, et al. Type 2 diabetes risk is associated with poorer general health and mental health in women and men.  17th European Public Health Conference 2024; Lisbon, Portugal: European Journal of Public Health; 2024. doiI: 10.1093/eurpub/ckae144.1291”

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Additional Editor Comments:

Dear authors

The following points need explanation

1: Verbal consent is usually unacceptable, and simply will weaken the study. Add a brief sentence that using verbal consent will not weak the results

2: The data of waist circumference was generated from an equation using height, weight, sex, and age (ref. 37). Please add the marginal errors in using this equation

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Partly

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2. Has the statistical analysis been performed appropriately and rigorously? -->?>

Reviewer #1: Yes

Reviewer #2: No

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3. Have the authors made all data underlying the findings in their manuscript fully available??>

The PLOS Data policy

Reviewer #1: No

Reviewer #2: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English??>

Reviewer #1: Yes

Reviewer #2: No

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Reviewer #1: Higher predicted type 2 diabetes risk is associated with worse mental health and self-rated general health among adults without known diabetes in Germany – Results of the nationwide population-based study GEDA 2022

Telephone interviews of around 5000 german adults. 5-year diabetes risk was determined with German Diabetes Risk Score and self rated health and mental health was examined depending on risk group. Depressive and anxiteysymptoms were more common among those with high risk of diabetes. The study is soundly conducted, but may benefit from further highlighting how it adds to current knowledge.

Comments

Major:

1. Please add a characteristics table (as table 1) stratified by diabetes risk classification.

2. ”We hypothesized that individuals with a higher predicted 5-year T2D risk are less likely to have favourable SRH and SRMH”. This is not tested in Table 3. Instead you test excellent SRH and SRMH. Please harmonize hypothesis and test. Perhaps the outcomes tested in table 3 should be poos SRH and SRMH? Alternatively, that the hypothesis is revised to state that excellent SRH and SRMH are less common among those with high diabetes risk?

3. Please

Minor:

1. It is stated in the introduction that diabetes is characterized by high glucose and caused by insulin resistance. An alternative statement would be that it is defined by high glucose and caused by a combination of life-style and genetic risk-factors. As you later discuss life-style it would be good to also highlight the importance of this factor in the introduction in a similar fashion as you now do for life-style and mental health.

2. You state that you adress a research gap with this paper. Please present what is currently known about this overlap, and also present what current guidelines from EASD and ADA say about addressing mental health in diabetes.

3. This statement in the discussion should be revised: ”epidemiological research on the association of T2D risk, comprising multiple lifestyle-related and biological risk factors, with SRH is scarce.”. There is extensive research in this area, please rephrase or be more specific with objective statements of quantity.

4. Please avoid the use of cardiometabolic health. This is not what you have been studying specifically. There are uncertainties in telephone interviews, predictive instruments and self reported health. Adding another layer of uncertainty by using a loosely defined term such as cardiometabolic health only increases the uncertainty of the study with no added benefit.

Reviewer #2: methods & statistics

1) Clarify the regression specification (robust variance + survey design).

You analyze binary outcomes with Poisson regression to obtain prevalence ratios (PRs). That’s fine if you’re using modified Poisson with a robust (sandwich) variance, ideally in a survey framework. Please state explicitly that you used robust standard errors and how the survey design was set (svyset in Stata: weights, PSUs, strata; variance estimator). At present it only says “the survey procedure” and “Poisson regression” without variance details, which matters for PR CIs and p-values [L159-L167][L171-L179]. See PLOS ONE’s statistical reporting guidance and standard references on modified Poisson.

2) Justify the choice of covariates (risk-score components vs confounders).

The exposure (GDRS) already bundles age, smoking, diet, etc. When you additionally adjust for age (and sometimes variables causally related to lifestyle, e.g., social support), you risk overadjustment or conditioning on mediators. Please include a brief causal rationale (e.g., a DAG) for what you adjust for and why. PLOS encourages transparent confounder rationale in line with STROBE.

3) Dealing with missing data.

Model 4 drops cases with missing education/living alone/social support (n=150; ~3%); please report the model-specific analytic N directly in Table 3 and consider multiple imputation to limit bias if missingness isn’t completely at random [L64-L66][L243-L248].

4) Bivariable vs adjusted inconsistencies (suppression by age).

You explain the anxiety finding as a suppression effect when adjusting for age—good. Consider adding a short supplemental table with correlations between age, GDRS, and outcomes to make this concrete (readers unfamiliar with suppression will appreciate that) [L288-L294]. A one-sentence textbook-style note would help.

5) Distributional reporting of the exposure.

You report the geometric mean of the predicted 5-year risk (1.15%). For readers, the median (IQR) and a simple histogram of predicted risk would be more interpretable; consider adding both. Also, clearly state the scale of the log-transform used in sensitivity analyses (natural log) and report the effect per 1 SD of log-risk for comparability [L185-L192][L249-L257].

6) Imputed waist circumference inside GDRS.

Waist was estimated from height/weight/age/sex using a prior equation; that’s acceptable, but it can shift risk categorization. Please (a) state the predictive performance (R²/RMSE) of the equation you used, (b) do a sensitivity analysis replacing GDRS with a version that omits waist (or uses BMI) to show robustness, and (c) discuss potential misclassification bias [L121-L127. The GDRS validation and simplified versions are good anchors to cite.

7) Statistical reporting format.

Adopt the journal’s preferred style: report PR (95% CI) with consistent decimals and avoid “95%-CI” and “PR1” notations. PLOS’s stats guidance asks for consistent reporting of regression results and measures of variance. See also PLOS ONE’s submission guidelines (statistical reporting section).

Presentation (tables/“graphs”)

Figures: I don’t see any figures/plots in the main text; the manuscript currently presents results via Tables 1–3. Consider adding a forest plot of adjusted PRs (Model 4) for each outcome with risk categories on the y-axis; this would visually summarize your key findings and is a common, reader-friendly presentation in PLOS ONE.

Tables (specific fixes):

• Table 1—category label inconsistency. The text defines SRH categories as “very good/good” vs “fair/bad/very bad,” but Table 1 uses “Average/poor/very poor.” Please align wording (use “Fair/Bad/Very bad” or “Fair/Poor/Very poor” consistently) [L31-L37][L131-L137][L135-L141][L135-L141].

• Table 1—typo in confidence interval. Region “South” shows 29.7 (27-7–31.8); should be 29.7 (27.7–31.8)[L155-L160].

• Table 2—formatting. Use 95% CI not “95%-CI”; ensure a uniform number of decimals across percentages and CIs, and consider reporting exact p to 3 decimals except where p<0.001 [L204-L207].

• Table 3—footnote style. The column header currently shows “PR1 (95%-CI)” while footnote 1 explains the models. Change “PR1” in the header to “PR” and keep the superscript/footnote on the table title or at the end (to avoid reading it as a variable name) [L241-L248][L245-L248].

• Model Ns. Provide the analytic N for each model row block (Model 1–4) since excluding covariate missings changes sample size [L243-L248].

Line-by-line language & style edits (with exact lines)

Note: PLOS doesn’t enforce US vs UK spelling, but they want consistent English throughout. You currently mix “behavioural/favourable/organisation/generalised/anonymised” with American variants. I suggest standardizing to one dialect across the whole paper (examples below). PLOS also prefers “95% CI,” sentence case titles, and clean abbreviation definitions.

Title & front matter

• Short title capitalization looks fine. Ensure sentence case for full title (PLOS guideline) [L36-L37].

Keywords (capitalization consistency):

• “anxiety symptoms; Depressive Symptoms; German Diabetes Risk Score; Population-based survey; Subjective health” → make consistent lowercase: “Anxiety symptoms; depressive symptoms; German Diabetes Risk Score; population-based survey; subjective health.” [L41-L43].

Abstract

• “telephone-interview survey” → telephone interview survey [L35-L36].

• Risk categories: replace “>=10%” with ≥10% (Unicode symbol) for consistency with journal style; similarly for other inequality signs [L36-L39].

• “Poisson regression was used … adjusting for …” → “… and models were adjusted for …” (active, parallel wording) [L39-L41].

• “95% confidence interval, CI” → “95% confidence interval (CI)” [L42-L44].

Introduction

• “etiologically heterogenous chronic disorder” → heterogeneous [L46-L51].

• Consistency: Decide on behavioral vs behavioural and use one form; e.g., “behavioral-related” rather than “behavioural-related” (several instances) [L77-L84].

• Minor: “e. g.” → e.g. (no spaces) [L65-L72].

Methods—Design & participants

• “German speaking resident adult population” → German-speaking [L87-L93].

• “computer-assisted telephone interview (CATI)” already defined—good.

• Ethics tense/consistency: “All participants … must give their verbal consent …” → “… gave their verbal consent …” (past tense) [L101-L107].

• “anonymised transfer” → anonymized (if choosing US spelling) [L103-L107].

• GDPR citation format: “Art. 7 No. 1” → consider “Article 7(1)” for standard legal style [L107-L110].

Methods—Exposure & outcomes

• SRH operationalization: consistent with WHO/MEHM; keep wording aligned with the categories you actually use in tables (see Table 1 point) [L129-L137].

• SRMH: “combined to” → combined into; and your second category title uses “good/fair/poor” while the original response option is “bad”—use “good/fair/bad” or stick to “good/fair/poor” but then reflect that in the prompt text; be consistent across text and tables [L31-L37].

• PHQ-2 / GAD-2 cut-offs: prefer “cutoff” (noun) or “cut-off”; you currently use “cut off” (two words) in several places [L53-L55][L61-L63].

• “Generalised Anxiety Disorder-2 (GAD-2)” → Generalized if adopting US spelling; the instrument name is commonly styled “Generalized Anxiety Disorder-2–item (GAD-2)” in US journals [L57-L61].

Methods—Statistics

• “Rao-Scott-Chi-Square test” → Rao–Scott chi-square test (en dash; lower-case chi-square) [L166-L170].

• “Prevalence Ratios (PR)” → prevalence ratios (PRs); keep pluralization consistent [L171-L179].

• “We utilise Poisson regression …” → utilize or simply use; avoid mixed dialects [L171-L179].

• Spell out design elements of svy (weights/PSU/strata, variance estimator) as noted above.

Results

• Minor discrepancy: text says “A total of 71% self-rated …” while Table 1 shows 72.0%. Harmonize (rounding) [L189-L192][L173-L180].

• Reporting style: keep a uniform decimal precision across proportions and CIs in text (e.g., one decimal for percentages; two for CIs), and always as % (95% CI: a–b) [L197-L205].

Tables

• Table 1: fix CI typo 29.7 (27.7–31.8) for South region [10:L155-L160].

• Table 2 & 3: Use 95% CI (no hyphen) and avoid “PR1” in headers; place the footnote marker after the table title instead [L204-L207][L241-L248].

Discussion

• Great that you note suppression and bidirectionality. Consider adding one citation on modified Poisson/log-binomial vs logistic for PRs to help readers less familiar with PR estimation in cross-sectional data.

One-page list of quick textual fixes (by line)

• Heterogenous → heterogeneous [11:L46-L51]

• telephone-interview survey → telephone interview survey [16:L35-L36]

• 95%-CI → 95% CI (everywhere)[12:L204-L207]

• PR1 (95%-CI) → PR (95% CI) (Table 3 header)[14:L241-L248]

• >=10% → ≥10% (risk thresholds)[16:L36-L39]

• must give … consent → gave … consent (past tense)[2:L101-L107]

• anonymised → anonymized (or make all spellings UK; be consistent)[2:L103-L107]

• e. g. → e.g.[13:L65-L72]

• Generalised → Generalized (if US spelling)[1:L57-L61]

• cut off → cutoff / cut-off (noun)[1:L53-L55][1:L61-L63]

• Rao-Scott-Chi-Square → Rao–Scott chi-square[9:L166-L170]

• behavioural-related → behavioral-related (or standardize to UK throughout)[13:L77-L84]

• SRMH categories: ensure text and tables match (avoid “Average/poor/very poor” if the described options are “fair/bad/very bad”)[1:L31-L37][10:L131-L137]

• Table 1 South CI typo: 29.7 (27.7–31.8)[10:L155-L160]

• 71% vs 72% SRH prevalence: harmonize rounding[9:L189-L192][10:L173-L180]

Bottom-line assessment

• Strengths: Timely national surveillance topic; appropriate use of a validated risk score (GDRS) in a large, weighted sample; consistent inverse associations for SRH/SRMH and positive associations for depressive/anxiety symptoms; thoughtful note on suppression by age.

• Main revisions needed: Fully specify regression variance/design, tighten reporting to PLOS style, fix a few table/text inconsistencies/typos, and add small sensitivity analyses (especially around the imputed waist component of GDRS and exposure scaling). A compact forest plot would also upgrade readability.

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Higher predicted type 2 diabetes risk is associated with worse mental health and self-rated general health among adults without known diabetes in Germany – Results of the nationwide population-based study GEDA 2022

PONE-D-25-38400R1

Dear Dr. Laura Neuperdt,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Kind regards,

Marwan Salih Al-Nimer, MD, PhD

Academic Editor

PLOS ONE

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