| Title: | Association of weight change with cardiovascular events and all-cause mortality in obese participants with cardiovascular disease: a prospective cohort study |
| Journal: | Heart |
| Published: | 16 Jan 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/39819616/ |
| DOI: | https://doi.org/10.1136/heartjnl-2024-324383 |
Publication 14503
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Abstract
BACKGROUND: Studies have examined the association between weight change and risk of cardiovascular (CV) outcomes in the general population. However, very few literature reported the association among obese people with established CV disease (CVD) and the factors associated with weight change are not clear. We sought to investigate this using the UK Biobank data.</p>
METHODS: In this large prospective population-based cohort study, absolute interval change scores in weight were calculated between weight measurements at baseline and the follow-up. The estimated HRs with 95% CIs were obtained from the Cox regression models to assess the association between weight change and the risk of CV death, cerebrovascular and ischaemic heart diseases and all-cause mortality.</p>
RESULTS: Of the 8297 obese participants who had CVD with repeated weight measurements, 43.1% were female. The mean age was 56.6 (SD: 7.2) years. The overall median follow-up of the study was 13.9 (IQR: 13.1-14.6) years. 52.7% of the participants had stable weight change (weight loss or gain<5 kg), 14.2% had large weight loss (≥10 kg) and 5.1% had large weight gain (≥10 kg). Compared with stable weight, only large weight gain was associated with an increased risk of CV death and all-cause mortality (fully adjusted HR (95% CI): 3.05 (1.40 to 6.67) for CV death and 1.93 (1.15 to 3.26) for all-cause mortality).</p>
CONCLUSIONS: Among obese individuals with CVD, large weight gain is associated with a higher risk of CV death and all-cause mortality. Further studies are needed to understand the exact mechanisms underlying the associations between weight loss or weight gain and mortality.</p>
3 Authors
- Jufen Zhang
- Rudolph Schutte
- Barbara Pierscionek
1 Application
| Application ID | Title |
|---|---|
| 98651 | Genetic and lifestyle risk factors and their interaction in the prediction of end-organ damage - a conventional and machine-learning analytical approach |
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