scholarly journals Body mass index and risk of obesity‐related conditions in a cohort of 2.9 million people: Evidence from a UK primary care database

2020 ◽  
Author(s):  
Christiane L. Haase ◽  
Kirsten T. Eriksen ◽  
Sandra Lopes ◽  
Altynai Satylganova ◽  
Volker Schnecke ◽  
...  
Vaccine ◽  
2021 ◽  
Author(s):  
Robert Neil F. Leong ◽  
James G Wood ◽  
Bette Liu ◽  
Robert Menzies ◽  
Anthony T. Newall

2013 ◽  
Vol 71 (Suppl 3) ◽  
pp. 119.1-119
Author(s):  
L. Cavagna ◽  
G. Trifirò ◽  
R. Caporali ◽  
P. Morabito ◽  
C. Ferrajolo ◽  
...  

2011 ◽  
Vol 21 (7) ◽  
pp. 725-732 ◽  
Author(s):  
C. Welch ◽  
I. Petersen ◽  
K. Walters ◽  
R. W. Morris ◽  
I. Nazareth ◽  
...  

2019 ◽  
Author(s):  
Christina Hansen Edwards ◽  
Eline Aas ◽  
Jonas Minet Kinge

Abstract Background: Overweight and obesity is a major global public health challenge, and understanding the implications for healthcare systems is essential for policy planning. Past studies have typically found positive associations between obesity and healthcare utilization, but these studies have not taken into consideration that obesity is also associated with early mortality. We examined associations between body mass index (BMI, reported as kg/m2) and healthcare utilization with and without taking BMI-specific survival into consideration. Methods: We used nationally representative data on 33 882 adults collected between 2002 and 2015. We computed BMI- and age-specific primary and secondary care utilization and multiplied the estimated values with gender-, age-, and BMI-specific probabilities of surviving to each age. Then, we summed the average BMI-specific utilization between 18 and 85 years. Results: During a survival-adjusted lifetime, males with normal weight (BMI: 18.5–24.9) had, on average, 167 primary care, and 77 secondary care contacts. In comparison, males with overweight (BMI: 25.0–29.9), category I obesity (BMI: 30.0–34.9), and category II/III obesity (BMI ≥35.0) had 11%, 41%, and 102% more primary care, and 14%, 29%, and 78% more secondary care contacts, respectively. Females with normal weight had, on average, 210 primary care contacts and 91 secondary care contacts. Females with overweight, category I obesity, and category II/III obesity had 20%, 34%, and 81% more primary care contacts, and 26%, 16%, and 16% more secondary care contacts, respectively. Conclusion: The positive association between BMI and healthcare utilization was reduced, but not offset, when BMI-specific survival was taken into consideration. Our findings underpin previous research and suggest that interventions to offset the increasing prevalence of overweight, and especially obesity, are warranted.


2018 ◽  
Vol 25 (1) ◽  
pp. 19-26 ◽  
Author(s):  
Sarah Carsley ◽  
Catherine S. Birken ◽  
Patricia C. Parkin ◽  
Eleanor Pullenayegum ◽  
Karen Tu

BackgroundElectronic medical records (EMRs) from primary care may be a feasible source of height and weight data. However, the use of EMRs in research has been impeded by lack of standardisation of EMRs systems, data access and concerns about the quality of the data.ObjectivesThe study objectives were to determine the data completeness and accuracy of child heights and weights collected in primary care EMRs, and to identify factors associated with these data quality attributes.MethodsA cross-sectional study examining height and weight data for children <19 years from EMRs through the Electronic Medical Record Administrative data Linked Database (EMRALD), a network of family practices across the province of Ontario. Body mass index z-scores were calculated using the World Health Organization Growth Standards and Reference.ResultsA total of 54,964 children were identified from EMRALD. Overall, 93% had at least one complete set of growth measurements to calculate a body mass index (BMI) z-score. 66.2% of all primary care visits had complete BMI z-score data. After stratifying by visit type 89.9% of well-child visits and 33.9% of sick visits had complete BMI z-score data; incomplete BMI z-score was mainly due to missing height measurements. Only 2.7% of BMI z-score data were excluded due to implausible values.ConclusionsData completeness at well-child visits and overall data accuracy were greater than 90%. EMRs may be a valid source of data to provide estimates of obesity in children who attend primary care.


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