Association between Long-Term Changes in Dietary Percentage of Energy from Fat and Obesity: Evidence from over 20 Years of Longitudinal Data
Objectives: This study assessed the associations between long-term trajectories of percentage of energy from fat (PEF) and obesity among Chinese adults. Methods: Longitudinal data collected by the China Health and Nutrition Survey from 1991 to 2015 were analyzed. A body mass index ≥28.0 was defined...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-08-01
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| Series: | Nutrients |
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| Online Access: | https://www.mdpi.com/2072-6643/14/16/3373 |
| _version_ | 1797408488186445824 |
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| author | Chenlu Wu Baibing Mi Wanrong Luo Binghua Chen Jiao Ma Hao Huang Qian Zhang Yaqiong Wang Heng Liu Binguo Yan Fangyao Chen Leilei Pei Ruru Liu Xueying Qin Duolao Wang Hong Yan Yaling Zhao |
| author_facet | Chenlu Wu Baibing Mi Wanrong Luo Binghua Chen Jiao Ma Hao Huang Qian Zhang Yaqiong Wang Heng Liu Binguo Yan Fangyao Chen Leilei Pei Ruru Liu Xueying Qin Duolao Wang Hong Yan Yaling Zhao |
| author_sort | Chenlu Wu |
| collection | DOAJ |
| description | Objectives: This study assessed the associations between long-term trajectories of percentage of energy from fat (PEF) and obesity among Chinese adults. Methods: Longitudinal data collected by the China Health and Nutrition Survey from 1991 to 2015 were analyzed. A body mass index ≥28.0 was defined as general obesity. Participants’ baseline PEF levels were categorized as lower than the recommendation of the Chinese Dietary Guideline (<20%), meeting the recommendation (20–30%), and higher than the recommendation (>30%). Patterns of PEF trajectories were identified by latent class trajectory analysis for overall participants and participants in different baseline PEF groups, respectively. Cox proportional hazards regression models with shared frailty were used to estimate associations between PEF and obesity. Results: Data on 13,025 participants with 72,191 visits were analyzed. Four patterns of PEF trajectory were identified for overall participants and participants in three different baseline PEF groups, respectively. Among overall participants, compared with “Baseline Low then Increase Pattern” (from 12% to 20%), participants with “Baseline Normal-Low then Increase-to-High Pattern” (from 20% to 32%) had a higher hazard of obesity (hazard ratio (HR) and 95% confident interval (CI) at 1.18 (1.01–1.37)). Compared with the “Stable Pattern” group (stable at around 18% and 22%, respectively), participants with “Sudden-Increase Pattern” (from 18% to 30%) in the baseline group whose PEF levels were lower than the recommendation and those with “Sudden-Increase then Decrease Pattern” (rapidly increased from 25% to 40%, and then decreased) in the baseline group who met the recommendation had higher hazards of obesity (HRs and 95% CIs being 1.65 (1.13–2.41) and 1.59 (1.03–2.46), respectively). Conclusions: Adults with a trajectory that involved a sudden increase to a high-level PEF had a higher risk of general obesity. People should avoid increasing PEF suddenly. |
| first_indexed | 2024-03-09T04:00:10Z |
| format | Article |
| id | doaj.art-215d403d24c646a8908aae9e967e543a |
| institution | Directory Open Access Journal |
| issn | 2072-6643 |
| language | English |
| last_indexed | 2024-03-09T04:00:10Z |
| publishDate | 2022-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Nutrients |
| spelling | doaj.art-215d403d24c646a8908aae9e967e543a2023-12-03T14:14:33ZengMDPI AGNutrients2072-66432022-08-011416337310.3390/nu14163373Association between Long-Term Changes in Dietary Percentage of Energy from Fat and Obesity: Evidence from over 20 Years of Longitudinal DataChenlu Wu0Baibing Mi1Wanrong Luo2Binghua Chen3Jiao Ma4Hao Huang5Qian Zhang6Yaqiong Wang7Heng Liu8Binguo Yan9Fangyao Chen10Leilei Pei11Ruru Liu12Xueying Qin13Duolao Wang14Hong Yan15Yaling Zhao16Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, No. 76, Yanta West Road, Xi’an 710061, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, No. 76, Yanta West Road, Xi’an 710061, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, No. 76, Yanta West Road, Xi’an 710061, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, No. 76, Yanta West Road, Xi’an 710061, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, No. 76, Yanta West Road, Xi’an 710061, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, No. 76, Yanta West Road, Xi’an 710061, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, No. 76, Yanta West Road, Xi’an 710061, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, No. 76, Yanta West Road, Xi’an 710061, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, No. 76, Yanta West Road, Xi’an 710061, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, No. 76, Yanta West Road, Xi’an 710061, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, No. 76, Yanta West Road, Xi’an 710061, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, No. 76, Yanta West Road, Xi’an 710061, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, No. 76, Yanta West Road, Xi’an 710061, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, No. 38, Xueyuan Road, Haidian District, Beijing 100191, ChinaDepartment of Clinical Sciences, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool L3 5QA, UKDepartment of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, No. 76, Yanta West Road, Xi’an 710061, ChinaDepartment of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Center, No. 76, Yanta West Road, Xi’an 710061, ChinaObjectives: This study assessed the associations between long-term trajectories of percentage of energy from fat (PEF) and obesity among Chinese adults. Methods: Longitudinal data collected by the China Health and Nutrition Survey from 1991 to 2015 were analyzed. A body mass index ≥28.0 was defined as general obesity. Participants’ baseline PEF levels were categorized as lower than the recommendation of the Chinese Dietary Guideline (<20%), meeting the recommendation (20–30%), and higher than the recommendation (>30%). Patterns of PEF trajectories were identified by latent class trajectory analysis for overall participants and participants in different baseline PEF groups, respectively. Cox proportional hazards regression models with shared frailty were used to estimate associations between PEF and obesity. Results: Data on 13,025 participants with 72,191 visits were analyzed. Four patterns of PEF trajectory were identified for overall participants and participants in three different baseline PEF groups, respectively. Among overall participants, compared with “Baseline Low then Increase Pattern” (from 12% to 20%), participants with “Baseline Normal-Low then Increase-to-High Pattern” (from 20% to 32%) had a higher hazard of obesity (hazard ratio (HR) and 95% confident interval (CI) at 1.18 (1.01–1.37)). Compared with the “Stable Pattern” group (stable at around 18% and 22%, respectively), participants with “Sudden-Increase Pattern” (from 18% to 30%) in the baseline group whose PEF levels were lower than the recommendation and those with “Sudden-Increase then Decrease Pattern” (rapidly increased from 25% to 40%, and then decreased) in the baseline group who met the recommendation had higher hazards of obesity (HRs and 95% CIs being 1.65 (1.13–2.41) and 1.59 (1.03–2.46), respectively). Conclusions: Adults with a trajectory that involved a sudden increase to a high-level PEF had a higher risk of general obesity. People should avoid increasing PEF suddenly.https://www.mdpi.com/2072-6643/14/16/3373percentage of energy from fatobesitylongitudinal datatrajectory |
| spellingShingle | Chenlu Wu Baibing Mi Wanrong Luo Binghua Chen Jiao Ma Hao Huang Qian Zhang Yaqiong Wang Heng Liu Binguo Yan Fangyao Chen Leilei Pei Ruru Liu Xueying Qin Duolao Wang Hong Yan Yaling Zhao Association between Long-Term Changes in Dietary Percentage of Energy from Fat and Obesity: Evidence from over 20 Years of Longitudinal Data Nutrients percentage of energy from fat obesity longitudinal data trajectory |
| title | Association between Long-Term Changes in Dietary Percentage of Energy from Fat and Obesity: Evidence from over 20 Years of Longitudinal Data |
| title_full | Association between Long-Term Changes in Dietary Percentage of Energy from Fat and Obesity: Evidence from over 20 Years of Longitudinal Data |
| title_fullStr | Association between Long-Term Changes in Dietary Percentage of Energy from Fat and Obesity: Evidence from over 20 Years of Longitudinal Data |
| title_full_unstemmed | Association between Long-Term Changes in Dietary Percentage of Energy from Fat and Obesity: Evidence from over 20 Years of Longitudinal Data |
| title_short | Association between Long-Term Changes in Dietary Percentage of Energy from Fat and Obesity: Evidence from over 20 Years of Longitudinal Data |
| title_sort | association between long term changes in dietary percentage of energy from fat and obesity evidence from over 20 years of longitudinal data |
| topic | percentage of energy from fat obesity longitudinal data trajectory |
| url | https://www.mdpi.com/2072-6643/14/16/3373 |
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