Table 5 The relationship between RFM and incident diabetes is analyzed using a two-piecewise Cox proportional hazards regression model in different sensitivity analyses.

From: Non-linear relationship between relative fat mass and diabetes risk in Japanese adults: a retrospective cohort study

Incident DM

Female

(HR, 95%CI, P)

Male

(HR, 95%CI, P)

All participants

(HR, 95%CI, P)

Model 4

   

Fitting model by standard linear regression

1.15 (1.05, 1.27) 0.0026

1.06 (0.99, 1.13) 0.1181

1.08 (1.03, 1.14) 0.0033

Fitting model by two-piecewise Cox proportional hazards regression

   

The inflection point of RFM

38.99

21.54

21.08

≤ Inflection point

1.12 (1.02, 1.23) 0.0141

0.95 (0.87, 1.04) 0.2724

0.96 (0.88, 1.05) 0.3448

> Inflection point

1.40 (1.18, 1.67) 0.0002

1.15 (1.05, 1.25) 0.0018

1.12 (1.06, 1.19) 0.0001

P for log-likelihood ratio test

0.011

0.002

0.003

Model 5

   

Fitting model by standard linear regression

1.13 (1.03, 1.24) 0.0104

1.04 (0.97, 1.12) 0.2628

1.07 (1.01, 1.14) 0.0143

Fitting model by two-piecewise Cox proportional hazards regression

   

The inflection point of RFM

38.66

23.29

22.29

≤ Inflection point

1.10 (1.00, 1.20) 0.0525

0.97 (0.89, 1.05) 0.4154

0.97 (0.89, 1.05) 0.3934

> Inflection point

1.42 (1.19, 1.68) < 0.0001

1.17 (1.06, 1.29) 0.0025

1.12 (1.05, 1.19) 0.0005

P for log-likelihood ratio test

0.003

0.001

0.001

  1. Model 4 was a sensitivity analysis in participants with age < 65 years.
  2. Model 5 was a sensitivity analysis conducted on participants with SBP < 140mmHg and DBP < 90mmHg.
  3. Note 1: In all participants, we adjusted gender, age, BMI, alcoholic intake, smoking status, exercise habits, SBP, DBP, ALT, AST, GGT, HDL-C, TC, TG, HbA1c, and FPG.
  4. Note 2: For female and male subgroups, we adjusted for age, BMI, alcoholic intake, smoking status, exercise habits, SBP, DBP, ALT, AST, GGT, HDL-C, TC, TG, HbA1c, and FPG.
  5. HR: hazard ratios; CI: confidence; DM: diabetes mellitus; RFM: relative fat mass
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