The use of anthropometric measures in the prediction of incident gout : results from a Swedish community-based cohort study
(2019) In Scandinavian Journal of Rheumatology 48(4). p.294-299- Abstract
Objectives: To study associations between different anthropometric measures and incident gout, and to find the best predictive measure. Method: We used the baseline investigation from the Malmö Diet and Cancer study, excluding cases of prevalent gout (n = 28 081). Cox regression for each anthropometric measurement was calculated per standard deviation increment for men and women, with hazard ratios (HRs) and 95% confidence intervals (CIs), using a hospital diagnosis of incident gout (M10) during follow-up as the outcome. Incremental C-statistics for each anthropometric measure were used to determine the measure with the best predictive capacity, in models adjusted for age, socio-economic data, lifestyle factors, comorbidities, and... (More)
Objectives: To study associations between different anthropometric measures and incident gout, and to find the best predictive measure. Method: We used the baseline investigation from the Malmö Diet and Cancer study, excluding cases of prevalent gout (n = 28 081). Cox regression for each anthropometric measurement was calculated per standard deviation increment for men and women, with hazard ratios (HRs) and 95% confidence intervals (CIs), using a hospital diagnosis of incident gout (M10) during follow-up as the outcome. Incremental C-statistics for each anthropometric measure were used to determine the measure with the best predictive capacity, in models adjusted for age, socio-economic data, lifestyle factors, comorbidities, and antihypertensive medications. Results: The study population included 11 049 men and 17 032 women, with 633 incident gout cases, 393 in men (3.6%) and 240 in women (1.4%). For both men and women, the five anthropometric measurements with highest C-statistics were weight, body mass index (BMI), waist circumference (WC), hip circumference, and waist-to-height ratio; in men, the measurement with the highest C-statistic was BMI (0.7361; fully adjusted HR 1.52, 95% CI 1.39–1.68), and in women WC (0.8085; fully adjusted HR 1.62, 95% CI 1.46–1.81). The increment in C-statistic with anthropometric measures was good, around 0.035. Waist-to-hip ratio, waist-to-hip-to-height ratio, body fat percentages, and especially A Body Shape Index had lower C-statistics. Conclusions: Both BMI and WC showed good predictive ability for incident gout. The clinically used cut-offs for BMI and WC appeared to be relevant in the assessment of increased risk of gout.
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- author
- Wändell, P. LU ; Andreasson, A. ; Hagström, H. ; Kapetanovic, M. C. LU and Carlsson, A. C.
- organization
- publishing date
- 2019-04-23
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Scandinavian Journal of Rheumatology
- volume
- 48
- issue
- 4
- pages
- 294 - 299
- publisher
- Taylor & Francis
- external identifiers
-
- pmid:31012370
- scopus:85064768194
- ISSN
- 0300-9742
- DOI
- 10.1080/03009742.2019.1583368
- language
- English
- LU publication?
- yes
- id
- ae9e5e95-5b49-4021-81dd-561b6218f724
- date added to LUP
- 2019-05-06 14:04:47
- date last changed
- 2024-04-16 04:25:57
@article{ae9e5e95-5b49-4021-81dd-561b6218f724,
abstract = {{<p>Objectives: To study associations between different anthropometric measures and incident gout, and to find the best predictive measure. Method: We used the baseline investigation from the Malmö Diet and Cancer study, excluding cases of prevalent gout (n = 28 081). Cox regression for each anthropometric measurement was calculated per standard deviation increment for men and women, with hazard ratios (HRs) and 95% confidence intervals (CIs), using a hospital diagnosis of incident gout (M10) during follow-up as the outcome. Incremental C-statistics for each anthropometric measure were used to determine the measure with the best predictive capacity, in models adjusted for age, socio-economic data, lifestyle factors, comorbidities, and antihypertensive medications. Results: The study population included 11 049 men and 17 032 women, with 633 incident gout cases, 393 in men (3.6%) and 240 in women (1.4%). For both men and women, the five anthropometric measurements with highest C-statistics were weight, body mass index (BMI), waist circumference (WC), hip circumference, and waist-to-height ratio; in men, the measurement with the highest C-statistic was BMI (0.7361; fully adjusted HR 1.52, 95% CI 1.39–1.68), and in women WC (0.8085; fully adjusted HR 1.62, 95% CI 1.46–1.81). The increment in C-statistic with anthropometric measures was good, around 0.035. Waist-to-hip ratio, waist-to-hip-to-height ratio, body fat percentages, and especially A Body Shape Index had lower C-statistics. Conclusions: Both BMI and WC showed good predictive ability for incident gout. The clinically used cut-offs for BMI and WC appeared to be relevant in the assessment of increased risk of gout.</p>}},
author = {{Wändell, P. and Andreasson, A. and Hagström, H. and Kapetanovic, M. C. and Carlsson, A. C.}},
issn = {{0300-9742}},
language = {{eng}},
month = {{04}},
number = {{4}},
pages = {{294--299}},
publisher = {{Taylor & Francis}},
series = {{Scandinavian Journal of Rheumatology}},
title = {{The use of anthropometric measures in the prediction of incident gout : results from a Swedish community-based cohort study}},
url = {{http://dx.doi.org/10.1080/03009742.2019.1583368}},
doi = {{10.1080/03009742.2019.1583368}},
volume = {{48}},
year = {{2019}},
}