Body mass index is the most useful predictive factor for the onset of nonalcoholic fatty liver disease : a community-based retrospective longitudinal cohort study
Background Nonalcoholic fatty liver disease (NAFLD) can progress to advanced liver disease and non-liver-related diseases. To prevent NAFLD onset, clinicians must be able to easily identify high-risk NAFLD patients so that intervention can begin at an earlier stage. We sought to identify the predict...
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| Vydáno v: | Journal of gastroenterology Ročník 48; číslo 3; s. 413 - 422 |
|---|---|
| Hlavní autoři: | , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Japan
Springer Japan
01.03.2013
Springer Springer Nature B.V |
| Témata: | |
| ISSN: | 0944-1174, 1435-5922, 1435-5922 |
| On-line přístup: | Získat plný text |
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| Abstract | Background
Nonalcoholic fatty liver disease (NAFLD) can progress to advanced liver disease and non-liver-related diseases. To prevent NAFLD onset, clinicians must be able to easily identify high-risk NAFLD patients so that intervention can begin at an earlier stage. We sought to identify the predictive factors for NAFLD onset.
Methods
In a community-based, longitudinal design, the records of 6,403 Japanese subjects were reviewed to identify those meeting the criteria for NAFLD onset. Univariate and multivariate logistic regression analyses were used to identify predictive factors for NAFLD onset. The accuracy of different models was evaluated according to their areas under the receiver operating characteristic curves. Comparative risk analysis was performed using the Kaplan–Meier method.
Results
Multivariate analysis of 400 subjects who met the criteria for the onset of NAFLD during the observation period confirmed that body mass index (BMI) at baseline was the most useful predictive factor for NAFLD onset in both sexes. Cutoff levels of BMI for NAFLD onset were estimated at 23 kg/m
2
for men and 22.2 kg/m
2
for women. The cumulative onset rate of NAFLD was significantly higher in the high BMI group than in the low BMI group in both sexes (
P
< 0.001).
Conclusion
BMI was confirmed as the most useful predictive factor for NAFLD onset in both sexes; its cutoff levels were similar to those recommended by the World Health Organization for helping to prevent metabolic disease. An accurate BMI cutoff level will enable clinicians to identify subjects at risk for NAFLD onset. |
|---|---|
| AbstractList | Background: Nonalcoholic fatty liver disease (NAFLD) can progress to advanced liver disease and non-liver-related diseases. To prevent NAFLD onset, clinicians must be able to easily identify high-risk NAFLD patients so that intervention can begin at an earlier stage. We sought to identify the predictive factors for NAFLD onset. Methods: In a community-based, longitudinal design, the records of 6,403 Japanese subjects were reviewed to identify those meeting the criteria for NAFLD onset. Univariate and multivariate logistic regression analyses were used to identify predictive factors for NAFLD onset. The accuracy of different models was evaluated according to their areas under the receiver operating characteristic curves. Comparative risk analysis was performed using the Kaplan-Meier method. Results: Multivariate analysis of 400 subjects who met the criteria for the onset of NAFLD during the observation period confirmed that body mass index (BMI) at baseline was the most useful predictive factor for NAFLD onset in both sexes. Cutoff levels of BMI for NAFLD onset were estimated at 23 kg/m super(2) for men and 22.2 kg/m super(2) for women. The cumulative onset rate of NAFLD was significantly higher in the high BMI group than in the low BMI group in both sexes (P < 0.001). Conclusion: BMI was confirmed as the most useful predictive factor for NAFLD onset in both sexes; its cutoff levels were similar to those recommended by the World Health Organization for helping to prevent metabolic disease. An accurate BMI cutoff level will enable clinicians to identify subjects at risk for NAFLD onset. Nonalcoholic fatty liver disease (NAFLD) can progress to advanced liver disease and non-liver-related diseases. To prevent NAFLD onset, clinicians must be able to easily identify high-risk NAFLD patients so that intervention can begin at an earlier stage. We sought to identify the predictive factors for NAFLD onset. In a community-based, longitudinal design, the records of 6,403 Japanese subjects were reviewed to identify those meeting the criteria for NAFLD onset. Univariate and multivariate logistic regression analyses were used to identify predictive factors for NAFLD onset. The accuracy of different models was evaluated according to their areas under the receiver operating characteristic curves. Comparative risk analysis was performed using the Kaplanâ[euro]"Meier method. Multivariate analysis of 400 subjects who met the criteria for the onset of NAFLD during the observation period confirmed that body mass index (BMI) at baseline was the most useful predictive factor for NAFLD onset in both sexes. Cutoff levels of BMI for NAFLD onset were estimated at 23Â kg/m^sup 2^ for men and 22.2Â kg/m^sup 2^ for women. The cumulative onset rate of NAFLD was significantly higher in the high BMI group than in the low BMI group in both sexes (PÂ <Â 0.001). BMI was confirmed as the most useful predictive factor for NAFLD onset in both sexes; its cutoff levels were similar to those recommended by the World Health Organization for helping to prevent metabolic disease. An accurate BMI cutoff level will enable clinicians to identify subjects at risk for NAFLD onset.[PUBLICATION ABSTRACT] Nonalcoholic fatty liver disease (NAFLD) can progress to advanced liver disease and non-liver-related diseases. To prevent NAFLD onset, clinicians must be able to easily identify high-risk NAFLD patients so that intervention can begin at an earlier stage. We sought to identify the predictive factors for NAFLD onset.BACKGROUNDNonalcoholic fatty liver disease (NAFLD) can progress to advanced liver disease and non-liver-related diseases. To prevent NAFLD onset, clinicians must be able to easily identify high-risk NAFLD patients so that intervention can begin at an earlier stage. We sought to identify the predictive factors for NAFLD onset.In a community-based, longitudinal design, the records of 6,403 Japanese subjects were reviewed to identify those meeting the criteria for NAFLD onset. Univariate and multivariate logistic regression analyses were used to identify predictive factors for NAFLD onset. The accuracy of different models was evaluated according to their areas under the receiver operating characteristic curves. Comparative risk analysis was performed using the Kaplan-Meier method.METHODSIn a community-based, longitudinal design, the records of 6,403 Japanese subjects were reviewed to identify those meeting the criteria for NAFLD onset. Univariate and multivariate logistic regression analyses were used to identify predictive factors for NAFLD onset. The accuracy of different models was evaluated according to their areas under the receiver operating characteristic curves. Comparative risk analysis was performed using the Kaplan-Meier method.Multivariate analysis of 400 subjects who met the criteria for the onset of NAFLD during the observation period confirmed that body mass index (BMI) at baseline was the most useful predictive factor for NAFLD onset in both sexes. Cutoff levels of BMI for NAFLD onset were estimated at 23 kg/m2 for men and 22.2 kg/m2 for women. The cumulative onset rate of NAFLD was significantly higher in the high BMI group than in the low BMI group in both sexes (P < 0.001).RESULTSMultivariate analysis of 400 subjects who met the criteria for the onset of NAFLD during the observation period confirmed that body mass index (BMI) at baseline was the most useful predictive factor for NAFLD onset in both sexes. Cutoff levels of BMI for NAFLD onset were estimated at 23 kg/m2 for men and 22.2 kg/m2 for women. The cumulative onset rate of NAFLD was significantly higher in the high BMI group than in the low BMI group in both sexes (P < 0.001).BMI was confirmed as the most useful predictive factor for NAFLD onset in both sexes; its cutoff levels were similar to those recommended by the World Health Organization for helping to prevent metabolic disease. An accurate BMI cutoff level will enable clinicians to identify subjects at risk for NAFLD onset.CONCLUSIONBMI was confirmed as the most useful predictive factor for NAFLD onset in both sexes; its cutoff levels were similar to those recommended by the World Health Organization for helping to prevent metabolic disease. An accurate BMI cutoff level will enable clinicians to identify subjects at risk for NAFLD onset. Nonalcoholic fatty liver disease (NAFLD) can progress to advanced liver disease and non-liver-related diseases. To prevent NAFLD onset, clinicians must be able to easily identify high-risk NAFLD patients so that intervention can begin at an earlier stage. We sought to identify the predictive factors for NAFLD onset. In a community-based, longitudinal design, the records of 6,403 Japanese subjects were reviewed to identify those meeting the criteria for NAFLD onset. Univariate and multivariate logistic regression analyses were used to identify predictive factors for NAFLD onset. The accuracy of different models was evaluated according to their areas under the receiver operating characteristic curves. Comparative risk analysis was performed using the Kaplan-Meier method. Multivariate analysis of 400 subjects who met the criteria for the onset of NAFLD during the observation period confirmed that body mass index (BMI) at baseline was the most useful predictive factor for NAFLD onset in both sexes. Cutoff levels of BMI for NAFLD onset were estimated at 23 kg/m.sup.2 for men and 22.2 kg/m.sup.2 for women. The cumulative onset rate of NAFLD was significantly higher in the high BMI group than in the low BMI group in both sexes (P < 0.001). BMI was confirmed as the most useful predictive factor for NAFLD onset in both sexes; its cutoff levels were similar to those recommended by the World Health Organization for helping to prevent metabolic disease. An accurate BMI cutoff level will enable clinicians to identify subjects at risk for NAFLD onset. Background Nonalcoholic fatty liver disease (NAFLD) can progress to advanced liver disease and non-liver-related diseases. To prevent NAFLD onset, clinicians must be able to easily identify high-risk NAFLD patients so that intervention can begin at an earlier stage. We sought to identify the predictive factors for NAFLD onset. Methods In a community-based, longitudinal design, the records of 6,403 Japanese subjects were reviewed to identify those meeting the criteria for NAFLD onset. Univariate and multivariate logistic regression analyses were used to identify predictive factors for NAFLD onset. The accuracy of different models was evaluated according to their areas under the receiver operating characteristic curves. Comparative risk analysis was performed using the Kaplan–Meier method. Results Multivariate analysis of 400 subjects who met the criteria for the onset of NAFLD during the observation period confirmed that body mass index (BMI) at baseline was the most useful predictive factor for NAFLD onset in both sexes. Cutoff levels of BMI for NAFLD onset were estimated at 23 kg/m 2 for men and 22.2 kg/m 2 for women. The cumulative onset rate of NAFLD was significantly higher in the high BMI group than in the low BMI group in both sexes ( P < 0.001). Conclusion BMI was confirmed as the most useful predictive factor for NAFLD onset in both sexes; its cutoff levels were similar to those recommended by the World Health Organization for helping to prevent metabolic disease. An accurate BMI cutoff level will enable clinicians to identify subjects at risk for NAFLD onset. Background Nonalcoholic fatty liver disease (NAFLD) can progress to advanced liver disease and non-liver-related diseases. To prevent NAFLD onset, clinicians must be able to easily identify high-risk NAFLD patients so that intervention can begin at an earlier stage. We sought to identify the predictive factors for NAFLD onset. Methods In a community-based, longitudinal design, the records of 6,403 Japanese subjects were reviewed to identify those meeting the criteria for NAFLD onset. Univariate and multivariate logistic regression analyses were used to identify predictive factors for NAFLD onset. The accuracy of different models was evaluated according to their areas under the receiver operating characteristic curves. Comparative risk analysis was performed using the Kaplan-Meier method. Results Multivariate analysis of 400 subjects who met the criteria for the onset of NAFLD during the observation period confirmed that body mass index (BMI) at baseline was the most useful predictive factor for NAFLD onset in both sexes. Cutoff levels of BMI for NAFLD onset were estimated at 23 kg/m.sup.2 for men and 22.2 kg/m.sup.2 for women. The cumulative onset rate of NAFLD was significantly higher in the high BMI group than in the low BMI group in both sexes (P < 0.001). Conclusion BMI was confirmed as the most useful predictive factor for NAFLD onset in both sexes; its cutoff levels were similar to those recommended by the World Health Organization for helping to prevent metabolic disease. An accurate BMI cutoff level will enable clinicians to identify subjects at risk for NAFLD onset. Nonalcoholic fatty liver disease (NAFLD) can progress to advanced liver disease and non-liver-related diseases. To prevent NAFLD onset, clinicians must be able to easily identify high-risk NAFLD patients so that intervention can begin at an earlier stage. We sought to identify the predictive factors for NAFLD onset. In a community-based, longitudinal design, the records of 6,403 Japanese subjects were reviewed to identify those meeting the criteria for NAFLD onset. Univariate and multivariate logistic regression analyses were used to identify predictive factors for NAFLD onset. The accuracy of different models was evaluated according to their areas under the receiver operating characteristic curves. Comparative risk analysis was performed using the Kaplan-Meier method. Multivariate analysis of 400 subjects who met the criteria for the onset of NAFLD during the observation period confirmed that body mass index (BMI) at baseline was the most useful predictive factor for NAFLD onset in both sexes. Cutoff levels of BMI for NAFLD onset were estimated at 23 kg/m2 for men and 22.2 kg/m2 for women. The cumulative onset rate of NAFLD was significantly higher in the high BMI group than in the low BMI group in both sexes (P < 0.001). BMI was confirmed as the most useful predictive factor for NAFLD onset in both sexes; its cutoff levels were similar to those recommended by the World Health Organization for helping to prevent metabolic disease. An accurate BMI cutoff level will enable clinicians to identify subjects at risk for NAFLD onset. |
| Audience | Academic |
| Author | HIASA Yoichi UEDA Teruhisa TOKUMOTO Yoshio MIYAKE Teruki KUMAGI Teru FURUKAWA Shinya YAMAMOTO Shin KITAI Kohichiro ONJI Morikazu HIROOKA Masashi KOIZUMI Mitsuhito MATSUURA Bunzo ABE Masanori |
| Author_xml | – sequence: 1 givenname: Teruki surname: Miyake fullname: Miyake, Teruki organization: Department of Gastroenterology and Metabology, Ehime University Graduate School of Medicine – sequence: 2 givenname: Teru surname: Kumagi fullname: Kumagi, Teru organization: Department of Gastroenterology and Metabology, Ehime University Graduate School of Medicine – sequence: 3 givenname: Masashi surname: Hirooka fullname: Hirooka, Masashi organization: Department of Gastroenterology and Metabology, Ehime University Graduate School of Medicine – sequence: 4 givenname: Shinya surname: Furukawa fullname: Furukawa, Shinya organization: Department of Gastroenterology and Metabology, Ehime University Graduate School of Medicine – sequence: 5 givenname: Mitsuhito surname: Koizumi fullname: Koizumi, Mitsuhito organization: Department of Gastroenterology and Metabology, Ehime University Graduate School of Medicine, Ehime General Health Care Association – sequence: 6 givenname: Yoshio surname: Tokumoto fullname: Tokumoto, Yoshio organization: Department of Gastroenterology and Metabology, Ehime University Graduate School of Medicine – sequence: 7 givenname: Teruhisa surname: Ueda fullname: Ueda, Teruhisa organization: Department of Gastroenterology and Metabology, Ehime University Graduate School of Medicine – sequence: 8 givenname: Shin surname: Yamamoto fullname: Yamamoto, Shin organization: Department of Gastroenterology and Metabology, Ehime University Graduate School of Medicine – sequence: 9 givenname: Masanori surname: Abe fullname: Abe, Masanori organization: Department of Gastroenterology and Metabology, Ehime University Graduate School of Medicine – sequence: 10 givenname: Kohichiro surname: Kitai fullname: Kitai, Kohichiro organization: Ehime General Health Care Association – sequence: 11 givenname: Yoichi surname: Hiasa fullname: Hiasa, Yoichi organization: Department of Gastroenterology and Metabology, Ehime University Graduate School of Medicine – sequence: 12 givenname: Bunzo surname: Matsuura fullname: Matsuura, Bunzo organization: Department of Gastroenterology and Metabology, Ehime University Graduate School of Medicine – sequence: 13 givenname: Morikazu surname: Onji fullname: Onji, Morikazu email: onjimori@m.ehime-u.ac.jp organization: Department of Gastroenterology and Metabology, Ehime University Graduate School of Medicine |
| BackLink | https://cir.nii.ac.jp/crid/1573668925947320576$$DView record in CiNii https://www.ncbi.nlm.nih.gov/pubmed/22933183$$D View this record in MEDLINE/PubMed |
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| Keywords | Body mass index Nonalcoholic fatty liver disease Predictive factor Metabolic disorders |
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Clin Chem. 2007 Apr;53(4):686-92 – reference: 23325165 - J Gastroenterol. 2013 Apr;48(4):549 – reference: 11117562 - Dig Dis Sci. 2000 Oct;45(10):1929-34 – reference: 14614602 - J Gastroenterol. 2003;38(10):954-61 – reference: 15168770 - Intern Med. 2004 Apr;43(4):289-94 – reference: 19590708 - J Clin Biochem Nutr. 2009 Jul;45(1):56-67 – reference: 22331365 - J Gastroenterol. 2012 Jun;47(6):696-703 – reference: 12076877 - J Hepatol. 2002 Jul;37(1):154-60 – reference: 14633828 - Diabetes Care. 2003 Dec;26(12):3351-2 – reference: 15860248 - Diabetes Res Clin Pract. 2005 May;68(2):178-9 – reference: 15565570 - Hepatology. 2004 Dec;40(6):1387-95 |
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| Snippet | Background
Nonalcoholic fatty liver disease (NAFLD) can progress to advanced liver disease and non-liver-related diseases. To prevent NAFLD onset, clinicians... Nonalcoholic fatty liver disease (NAFLD) can progress to advanced liver disease and non-liver-related diseases. To prevent NAFLD onset, clinicians must be able... Background Nonalcoholic fatty liver disease (NAFLD) can progress to advanced liver disease and non-liver-related diseases. To prevent NAFLD onset, clinicians... Background: Nonalcoholic fatty liver disease (NAFLD) can progress to advanced liver disease and non-liver-related diseases. To prevent NAFLD onset, clinicians... |
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| Title | Body mass index is the most useful predictive factor for the onset of nonalcoholic fatty liver disease : a community-based retrospective longitudinal cohort study |
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