The Overweight and Obesity Landscape in France: Data from the French Cohort of the Multi-country IMPACT-O Study

Abstract

Introduction

The epIdeMiology landscape PAtient Care paThways of Obesity (IMPACT-O) study was a multi-country, retrospective cohort study that utilised healthcare databases to determine the landscape/impact of overweight and obesity. Here we describe the sociodemographic, clinical and treatment characteristics of adults with a first record of overweight/obesity or obesity in France.

Methods

This study utilised electronic medical records from the France longitudinal patient database (LPD) capturing data from general practitioners and specialist clinicians for 2018–2022. Included adults (≥ 18 years) had a diagnosis code and/or ≥ 1 body mass index of ≥ 25 kg/m² (overweight/obesity cohort) or ≥ 30 kg/m² (obesity cohort) and a ≥ 12-month observation period before and after their first record indicating overweight/obesity or obesity. Demographic and clinical parameters, including obesity-related complications (ORCs), as recorded by physicians contributing to the database, were described.

Results

Of 10,206,481 subjects in the France LPD, 93,714 were included in the overweight/obesity and 46,252 in the obesity cohort; of these, 58.9% and 63.1%, respectively, had ORCs. Hypertension was the most frequently recorded ORC for both cohorts (28.8% and 32.9%, respectively). The proportion of people receiving pharmacological therapies with an effect on weight was ≤ 3%; no lifestyle interventions or bariatric surgery were recorded.

Conclusion

These results highlight the high burden of ORCs in adults with overweight or obesity at first available record and the limited use of pharmacological treatment with an effect on weight. Improving weight-related data capture in centralised electronic medical records could facilitate the integration of multidisciplinary approaches and better support the management of obesity.

Graphical Abstract available for this article.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s12325-026-03589-1.

Plain Language Summary

This study evaluated information recorded in a database used by general practitioners and specialists in France to determine the general profile of people with overweight (mild excess weight, with a body mass index measurement higher than 25 kg/m² but less than 30 kg/m²) and obesity (more severe excess weight, with a body mass index higher than 30 kg/m²) when first diagnosed. It also looked into the common health issues present in this population, the treatments they receive, and the kinds of medical professionals involved in their care. People included in the analysis had an average age of around 53 years and were more likely to be female individuals. The number of additional health conditions present in people with overweight or obesity tended to increase with increasing excess weight. High blood pressure was one of the most common health conditions recorded among people with overweight and obesity. There were very few records of administration of medicines with an effect on weight in the database, and there were no records of recommendations by physicians to reduce weight by changing lifestyle or undergoing bariatric surgery. These results highlight the burden of health conditions in adults in France with overweight or obesity when first diagnosed and the limited recording of medicines with an effect on weight. Comprehensive and centralized documentation of weight-related data in medical notes could help to improve the care of people with overweight and obesity.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12325-026-03589-1.

Key Summary Points

Why carry out this study?

Obesity is associated with a number of health risks, such as type 2 diabetes, cardiovascular disease and mental health conditions, as well as negative impacts on health-related quality of life and an increased economic burden.

The prevalence of overweight and obesity in adults in France has been reported as 31% and 18%.

This study aimed to describe the real-world landscape/impact of overweight and obesity in France using data from electronic medical records for people with a first record of overweight or obesity between 2018 and 2022.

What was learned from this study?

There was a high burden of obesity-related complications in adults with overweight or obesity at first available record, particularly hypertension, dyslipidaemia, type 2 diabetes and depression, and a limited use of pharmacological treatment with an effect on weight. Patients were mostly managed by a general practitioner rather than a specialist.

Improving weight-related data capture in centralised electronic medical records could facilitate a more multidisciplinary approach and better support the management of obesity.

Digital Features

This article is published with digital features, including a graphical abstract, to facilitate understanding of the article. To view digital features for this article, go to 10.6084/m9.figshare.31746709.

Introduction

Obesity is a result of abnormal or excessive fat accumulation, and is described as a chronic, relapsing disease that presents a risk to overall health. Overweight is defined as a body mass index (BMI) ≥ 25 kg/m² and obesity is defined as a BMI ≥ 30 kg/m² [1]. A study in France in 2024 reported the prevalence of overweight and obesity in adults as 31% and 18%, respectively [2]. Furthermore, a steep increase in the prevalence of obesity in younger age groups (18–24 years and 18–29 years) has been noted in other studies [3, 4].

Obesity increases the risk of obesity-related complications (ORCs) such as type 2 diabetes (T2D), cardiovascular disease, mental health conditions, obstructive sleep apnoea and certain cancers [5]. People with obesity in the French CONSTANCES cohort study presented with more ORCs than people with normal weight [6]. In another analysis of the CONSTANCES cohort, obesity class (severity) affected healthcare utilisation, with people with class 3 obesity (BMI ≥ 40 kg/m²) more likely to visit emergency departments than those with class 1 obesity (BMI ≥ 30–35 kg/m²) [7].

Obesity also impacts health-related quality of life (HRQoL) and contributes to a greater economic burden in people with obesity than in people with normal weight [8, 9]. In addition to extra healthcare costs, people with obesity experienced higher percentages of absenteeism than people with normal weight [8]. A French study that assessed the impact of body size on employment found that women with obesity were less likely to be employed than women with normal weight despite having the same skill level [10].

In France, patient care pathways are set according to obesity severity, defined using a staging algorithm that goes beyond BMI to include associated metabolic, functional and psychological repercussions. Weight management is coordinated by a general practitioner (GP) for non-complex obesity focusing on lifestyle interventions, while specialists (endocrinologists and nutrition doctors) generally coordinate care for complex obesity in general settings or within centres specialised in obesity [11]. The latter are resource centres for patients with the most severe forms of obesity.

Currently, pharmacological treatment for obesity in France is restricted to glucagon-like peptide 1 receptor agonists (GLP-1 RAs) with an approved indication for weight management, such as liraglutide and semaglutide, and a lipase inhibitor, orlistat. Guidelines recommend restricting GLP-1 RAs to people with complex obesity after lifestyle interventions have failed to provide meaningful weight loss. Specifically, liraglutide is approved for weight management and has been marketed in France without reimbursement since 2021 [12], and semaglutide was approved for weight management in 2022 and has recently been marketed without reimbursement [13–16]. Tirzepatide was approved for weight management in France in November 2024 [15, 17]. Bariatric surgery has been proven to be highly effective in achieving and maintaining weight loss (up to 10 years) [18], but it is generally reserved for those with class 3 (defined above) or class 2 (BMI ≥ 35 to < 40 kg/m²) obesity with an associated ORC; however, the risk of surgical and nutritional complications should be considered [19].

While obesity prevalence continues to increase along with the associated burden of ORCs, which has economic- and HRQoL-related impacts [20], there is still limited real-world evidence on the disease burden from a country-level perspective. The use of data routinely recorded in electronic medical records (EMR), which can aid in understanding the real-world impacts of overweight and obesity, has not been fully explored before in France. The epIdeMiology landscape PAtient Care paThways of Obesity (IMPACT-O) multi-country study utilised existing EMR to estimate the extent of recording and describe the landscape and impact of overweight and obesity across selected countries in Europe and the Asia–Pacific region. The findings of the overall IMPACT-O study indicated that 22.0% of adults with at least one BMI recording in the France Longitudinal Patient Database (LPD) were identified with overweight or obesity, and, of these, only 2.9% had formal diagnosis codes in their EMR. Additionally, 60% of adults with overweight or obesity were reported to have at least one documented ORC [21].

Here we present further analyses of the French cohort of the IMPACT-O study. The aim of these analyses was to describe the real-world landscape and impact of overweight and obesity in France using data from EMR for people with a first record of overweight or obesity between 2018 and 2022. This included demographic and clinical parameters, ORCs, and treatments in this population, as recorded by physicians contributing to the database.

Methods

Study Design

The IMPACT-O study was a retrospective multi-country cohort study that used EMR and claims databases standardised to the Observed Medical Outcomes Partnership (OMOP) Common Data Model (CDM) from Australia, France, Germany, Italy, Spain, the UK and Japan. The methodology for the IMPACT-O study and the multi-country results have been previously described [21]. Cohorts were country-specific and were analysed independently. While the IMPACT-O program provided the overarching study design and cohort definitions, the analyses presented here are specific to France and were conducted independently of the multi-country results. The present descriptive cohort study used only data from the France LPD, as part of the IMPACT-O study, for the July 2023 data cut. Data coverage for the study period was 1 January 2018 to 30 September 2022.

All analyses performed in this study were conducted in accordance with Data Use Agreement terms as specified by the data owners. Reference made to the France LPD is intended to be descriptive of the data asset licensed by IQVIA. For the France database, there was no institutional review board applicable to the usage and dissemination of the results of this study or required registration of the protocol with additional ethics oversight. This study was performed in accordance with the Helsinki Declaration of 1964 and its later amendments.

Database

The France LPD is a computerised network of GPs and specialists who contribute to a centralised database of anonymised patient EMR [22, 23]. This study reports overall data for the combined GP and specialist datasets; since GP and specialist records are not linked, they constitute separate datasets. The extent of overlap between the two panels in terms of patient representation is less than 0.5%, which is small enough to not affect the results.

The database includes 17.5 million patients (27% of the French population) with 6200 GPs and 3000 specialists contributing to the database from select regional catchments without national coverage. The dates of service of the database include 2012 through to 2022.

Diagnoses and procedures were based on the International Classification of Diseases, tenth revision (ICD-10) mapped to Systematized Nomenclature of Medicine (SNOMED) codes in the OMOP CDM, and prescriptions were identified by France EMR codes; drug information was derived from prescriptions by clinicians. Observation time was defined by the first and last consultation dates.

Population

This analysis focused on two cohorts of people with new overweight or obesity records during the study period: the overweight/obesity and the obesity cohorts. The study aimed to describe the populations meeting the overweight/obesity and obesity criteria to understand the characteristics of these populations as a whole, and no comparisons between cohorts were intended.

The index date was defined as a person’s first record in the study period of either a diagnosis code or a BMI record that defined overweight/obesity or obesity. The overweight/obesity and the obesity cohorts were based on BMI and/or diagnosis codes with 12 months follow-up. The obesity/overweight cohort included people (≥ 18 years at index date) with at least one BMI record of ≥ 25 kg/m² and/or diagnosis codes of overweight/obesity with a follow-up period of ≥ 12 months pre- and post-index date. The obesity cohort included people with the same characteristics and follow-up data, but with at least one BMI record of ≥ 30 kg/m² and/or diagnosis code for obesity. People were excluded if there was missing age or gender, a BMI record that indicated non-overweight/non-obesity within 30 days pre- and post-index date or a BMI that indicated overweight (or obesity) at any time prior to the index date.

Variables

BMI classes were defined as follows: overweight, 25.0 to < 30.0 kg/m²; class 1 obesity, 30.0 to < 35.0 kg/m²; class 2 obesity, 35.0 to < 40.0 kg/m²; and class 3 obesity, ≥ 40 kg/m² [24]. Active individuals were defined as people with new records of overweight or obesity (including diagnosis, prescription, procedure, device, measurement or visit to care sites) recorded between 2018 and 2022 in the France LPD.

The France LPD has the capability to capture data for all clinical visits and includes fields to document various types of encounters. However, the actual data available for analysis are contingent upon the information entered by healthcare providers (HCPs) during real-world clinical encounters. As a result, while the database structure accommodates a wide range of data fields, some fields may contain few or no records if the corresponding information was not documented in the EMR. Baseline sociodemographic (age and gender) and clinical characteristics (BMI, cardiometabolic parameters and ORCs) are described for each cohort (Fig. 1).

Fig. 1.

Study design for the overweight/obesity and obesity cohorts. BMI body mass index

Selected ORCs were chosen based on guidance from previous literature, clinical guidance and the feasibility of identifying records indicating the presence of ORCs in the dataset. At an individual level, the presence of ORCs was identified by diagnosis codes or diagnosis codes and medication in cases where medication could be assigned to a specific disease and was available for analysis. The following ORCs were identified by a combination of diagnosis codes and medications: hypertension, dyslipidaemia, depression, anxiety and T2D. Pre-specified subgroup analyses were performed to compare the profile of adults aged < 65 versus ≥ 65 years and female versus male individuals. The number of clinician visits and the speciality of the clinician who first documented overweight or obesity at the index date are described for the overweight/obesity and obesity cohorts (Fig. 1). The clinician specialities included in the French cohort were GP, endocrinology, cardiology, obstetrics/gynaecology, pulmonary disease, gastroenterology, diabetic medicine and other speciality. It should be noted that specialties mapping in the France LPD does not differentiate between endocrinologists and diabetes medicine specialists who reported treating people with overweight or obesity. Interventions during the 12-month follow-up period, which included lifestyle interventions, pharmacological therapies with an effect on weight (defined as GLP-1 RAs, regardless of dose or indication, and orlistat) and bariatric surgery, and concomitant medications are described for the overweight/obesity and obesity cohorts.

Statistical Analyses

Considering the descriptive nature of the study, the sample size was determined by the availability of data and the number of subjects retrieved from the database rather than by a formal power calculation. Analyses were conducted using the OMOP analytical tools in structured query language through snowflake and R (https://www.r-project.org) [25]. Continuous data are described as mean, median and standard deviation, while categorical data are described as number and percentage distribution, including missing data as applicable. For the France LPD, a threshold of 10 people was required for presenting aggregated results because of General Data Protection Regulation rules. Results that are less than the threshold may be reported as < 10. Descriptive results are presented for each cohort.

Results

The France LPD is a combination of the France LPD GP (n = 6,525,398) and the France LPD specialist (n = 3,642,563) databases. A total of 10,206,481 active subjects were recorded in the overall France LPD. The overweight/obesity cohort included 93,714 (1%) people from the overall database (72,197 from GP LPD; 21,517 from specialist LPD); the obesity cohort included 46,252 (< 1%) people from the overall database (35,624 from GP LPD; 10,628 from specialist LPD) (Fig. 2).

Fig. 2.

Overweight/obesity and obesity cohort attrition, 2018–2022. BMI body mass index, GP general practitioner, LPD longitudinal patient database

Sociodemographic and Clinical Characteristics

People in the overweight/obesity cohort were a similar age to those in the obesity cohort (53.4 years and 52.9 years, respectively). In both cohorts, there were more female than male individuals, with a slightly higher proportion of female individuals in the obesity cohort than the overweight/obesity cohort (Table 1).

Table 1.

Sociodemographic and clinical characteristics of the overweight/obesity and the obesity cohorts, 2018–2022

	Overweight/obesity cohort (n = 93,714)	Obesity cohort (n = 46,252)
Age at index date, mean (SD), years	53.4 (17.3)	52.9 (16.7)
Gender, female, n (%)	50,057 (53.4)	26,557 (57.4)
Mean baseline BMI* (SD), kg/m2	30.0 (4.7)	34.0 (4.2)
ORC,† n (%)
Hypertension	27,008 (28.8)	15,224 (32.9)
Dyslipidaemia	15,642 (16.7)	8269 (17.9)
Depression	8325 (8.9)	4615 (10.0)
Anxiety	12,432 (13.3)	6464 (14.0)
T2D	9225 (9.8)	5786 (12.5)
Baseline cardiometabolic parameters, mean (SD)
HbA1c, %	6.8 (1.5)	6.9 (1.4)
Total cholesterol, mg/dL	95.5 (30.5)	95.2 (33.2)
Systolic blood pressure, mmHg	130.0 (15.4)	132.3 (15.7)
Diastolic blood pressure, mmHg	77.1 (10.3)	78.5 (10.5)

BMI body mass index, HbA1c glycated haemoglobin, ORCs obesity-related complications, SD standard deviation, T2D type 2 diabetes

*Within ± 60 days of the index date, closest to index date

^†Top five most frequently recorded ORCs, identified by diagnosis and medication (within 1 year before index date, including index date). See all ORCs in Supplementary Table S1

The mean BMI at baseline was 30.0 kg/m² for people in the overweight/obesity cohort and 34.0 kg/m² for people in the obesity cohort (Table 1). Most people in the overweight/obesity cohort had overweight (61.1%) while most people in the obesity cohort had class 1 obesity (70.9%) (Fig. 3a, b).

Fig. 3.

BMI categories for people in the overweight/obesity cohort (a) and the obesity cohort (b). BMI body mass index

The ORC burden was high in the overweight/obesity and obesity cohorts; 58.9% (n = 55,147) and 63.1% (n = 29,172) of people had at least one ORC, respectively (Fig. 4a). A high proportion of people in the overweight/obesity (32.7%) and obesity (36.5%) cohorts also had multimorbidity (at least two ORCs). Considering age, more adults in the ≥ 65 years subgroup had ≥ 1 ORC (overweight/obesity cohort, 71.6%; obesity cohort, 74.6%) than those in the < 65 years subgroup (overweight/obesity cohort, 53.6%; obesity cohort, 58.8%); adults in the obesity cohort had a higher ORC burden than those in the overweight/obesity cohort irrespective of age subgroup (Fig. 4b). Slight gender differences were observed in ORC burden between female and male individuals; 60.2% and 65.3% of male individuals in the overweight/obesity and obesity cohort, respectively, had ≥ 1 ORC while 57.6% and 61.4% of female individuals in the overweight/obesity and obesity cohort, respectively, had ≥ 1 ORC (Fig. 4c). Hypertension was the most frequently recorded ORC for people in both the overweight/obesity and the obesity cohorts with a recording rate of 28.8% and 32.9%, respectively, followed by dyslipidaemia (overweight/obesity, 16.7%; obesity, 17.9%), anxiety (overweight/obesity, 13.3%; obesity, 14,0%), T2D (overweight/obesity, 9.8%; obesity, 12.5%) and depression (overweight/obesity, 8.9%; obesity, 10.0%) (Table 1). Additional ORCs are detailed in Table S1 (online Supplementary Material).

Fig. 4.

The number of ORCs in the overweight/obesity and obesity cohorts (a) and the number of ORCs in the overweight/obesity and obesity cohorts presented by age group (b) and sex (c). ORCs obesity-related complications

Interventions and Clinician Involvement

While fields for lifestyle intervention and bariatric surgery were available in the France LPD, zero records of these interventions were captured for the included cohorts. In the overweight/obesity cohort and in the obesity cohort, the percentage of people who received pharmacological therapies with an effect on weight in the 12-month follow-up period was 1.9% and 3.0%, respectively. Of those receiving pharmacological therapies with an effect on weight, almost all were receiving GLP-1 RAs (overweight/obesity, 1.8%; obesity, 2.8%) followed by orlistat (overweight/obesity, 0.1%; obesity, 0.2%) (Table 2).

Table 2.

Interventions and specialist visits of people in the overweight/obesity and obesity cohorts, 2018–2022

	Overweight/obesity cohort (n = 93,714)	Obesity cohort (n = 46,252)
Interventions
Lifestyle interventions	0	0
Bariatric surgery	0	0
Pharmacological therapies with effects on weight,* n (%)
GLP-1 RAs	1640 (1.8)	1306 (2.8)
Orlistat	78 (0.1)	68 (0.2)
Concomitant medications,* n (%)
Antidiabetic treatments (including GLP-1 RAs)	8699 (9.3)	5560 (12.0)
Antihypertensives	27,930 (29.8)	15,659 (33.9)
Cardiovascular disease†	29,986 (32.0)	16,581 (35.9)
Dyslipidaemia medication	16,585 (17.7)	8772 (19.0)
Antidepressants and anxiolytics	15,254 (16.3)	7935 (17.2)
Specialist who documented first overweight/obesity diagnosis at index date, n (%)
GP	72,257 (77.1)	35,649 (77.1)
Endocrinology	3589 (3.8)	2066 (4.5)
Cardiology	7474 (8.0)	3831 (8.3)
Obstetrics/gynaecology	3125 (3.3)	1259 (2.7)
Pulmonary disease	1601 (1.7)	958 (2.1)
Gastroenterology	2548 (2.7)	1043 (2.3)
Diabetic medicine	3589 (3.8)	2066 (4.5)
Other speciality	3123 (3.3)	1447 (3.1)
Number of clinical visits,* mean (SD)
Any visits	4.9 (4.0)	5.2 (4.2)
GP visits	5.6 (4.1)	5.9 (4.3)
Endocrinology visits	3.9 (2.6)	3.9 (2.6)
Cardiology visits	1.8 (1.2)	1.7 (1.2)
Obstetrics/gynaecology visits	2.7 (2.9)	2.6 (2.9)
Pulmonary disease visits	2.8 (1.7)	2.7 (1.7)
Gastroenterology visits	2.4 (2.0)	2.6 (2.1)
Rheumatology visits	4.0 (3.2)	3.9 (3.2)
Other speciality visits	3.9 (3.8)	4.0 (3.4)

GLP-1 RAs glucagon-like peptide 1 receptor agonists, GP general practitioner, SD standard deviation

*In the 12-month follow-up period

^†Cardiovascular disease was identified by diagnosis code. Medications for cardiovascular disease were angiotensin-converting enzyme (ACE) inhibitors, angiotensin receptor blockers (ARBs), aspirin (acetylsalicylic acid), beta blockers, calcium channel blockers, diuretics and statins (3-hydroxy-3-methylglutaryl coenzyme A [HMG CoA] reductase inhibitors)

Concomitant medications for cardiovascular disease and antihypertensive medications (listed in Table S2, online Supplementary Material) were the most frequently identified concomitant medications for the overweight/obesity (32.0% and 29.8%, respectively) and obesity (35.9% and 33.9%, respectively) cohorts in the 12-month follow-up period.

The first documented overweight or obesity diagnosis was usually made by GPs for both cohorts (77.1%), followed by cardiologists (overweight/obesity, 8.0%; obesity, 8.3%) (Table 2). The mean number of clinical visits over the 12 months of follow-up was similar across both cohorts (overweight/obesity, 4.9; obesity, 5.2), with GP visits the most common (overweight/obesity, 5.6; obesity, 5.9 [Table 2]).

Discussion

The present analysis describes the sociodemographic and clinical characteristics, including ORC burden, interventions and clinician involvement in the management of people at first available record of overweight or obesity between 2018 and 2022 in the France LPD.

More than half of people in both the incident overweight/obesity and obesity cohorts had at least one ORC (numerically higher in the obesity cohort than the overweight cohort) at the first available record in the study period, and approximately one-third of adults in our study had two or more ORCs, indicating a high comorbidity burden. A French study of two nationwide representative surveys estimated the impact of multimorbidity (two or more comorbid conditions); their findings noted a higher prevalence in women and according to age, with the greatest increases in prevalence occurring between the age groups of 45–54 and 55–64 years, and 55–64 and 65–74 years [26]. In this study, ORC burden stratified by age revealed that numerically more people aged 65 and over had ≥ 1 ORC than those younger than 65 years, which is similar to the findings reported in the overall multi-country study [27].

Our study reports data related to the first record of a formal diagnosis of overweight or obesity within the EMR. Interestingly, a previous survey has shown that 57% of individuals with self-reported obesity had issues with their weight for at least 3 years (overall mean 6 years) before discussing weight management with an HCP, with such a delay potentially contributing to the development of ORCs [26]. Additionally, a recent survey found ORCs are often the catalyst for initiating discussions of weight management and treatments [28]. These results align with the results of the present study, and taken together they suggest that a formal diagnosis of obesity may be delayed and only formally acknowledged when ORCs are present, meaning that people with overweight or obesity without ORCs may therefore be underrepresented in the population of the current study and underrecognised by the healthcare system as a whole. It is possible that some of the ORCs captured in this study (e.g. anxiety) occurred before and not because of obesity, contributing to the development of excess weight. More data are needed to better understand the relationship between ORCs and the timing of the documentation, assessment and management of obesity, as well as the impact on outcomes.

In our study, hypertension, dyslipidaemia and anxiety were the top three recorded ORCs across both cohorts with numerically higher values for people in the obesity cohort. A study of six European countries, including France, also reported hypertension and dyslipidaemia as the top two most frequently reported ORCs, followed by T2D rather than anxiety, and noted an increase in the number of ORCs in adults in higher obesity classes [29, 30]. While more people in the obesity cohort were receiving concomitant medications for ORCs than people in the overweight/obesity cohort, both cohorts were mainly treated for cardiovascular disease.

While the present analysis provides an overview of the weight loss interventions in France, it is only partially captured for various reasons. Guidelines recommend lifestyle interventions and obesity management medications (OMM) for the treatment of overweight and obesity. For people with obesity, bariatric surgery (BMI ≥ 35 kg/m² with comorbidities or ≥ 40 kg/m²) is indicated after the failure of well-conducted medical management [17]. However, there were no records of lifestyle intervention or bariatric surgery in the France LPD, despite data fields being available for these interventions. One reason for the lack of recording of lifestyle interventions may be due to lack of reimbursement of such interventions in France; therefore, these are not routinely recorded in EMR. Another reason may be that lifestyle interventions were provided and recorded by nutritionists and dieticians at specialised centres with multidisciplinary teams outside of the France LPD. Evidence from a bariatric surgery analysis found bariatric surgeries increased fourfold in France between 2005 and 2014 [31, 32], suggesting that there would be a corresponding increase in bariatric surgery recording in EMR, which was not seen in the France LPD. The lack of bariatric surgery recordings in this study could be due to the larger proportion of GP data rather than specialist data present in the database, because GPs are less likely to manage people who receive bariatric surgery [33]. Furthermore, bariatric surgery is generally performed in centres specialised in obesity [34], which have not contributed to the France LPD. Patient management could be optimised with systematic recording of interventions (including structured diet and exercise programmes) and sharing of patient data across all disciplines/specialities responsible for weight management.

The precise evaluation of OMM use was limited for two reasons: firstly, the recording of GLP-1 RA use was independent of dose or indication and thus it was not possible to determine whether GLP-1 RAs were prescribed for the treatment of T2D or for weight loss from our data source. Secondly, for most of the study period (2018–2022), GLP-1 RAs were marketed and reimbursed in France for the indication of T2D only; liraglutide was only indicated for the treatment obesity from 2021. It is likely that GLP-1 RAs were prescribed primarily for the treatment of T2D.

The initial diagnosis of overweight or obesity was mainly made by GPs, and GPs also reported the most clinical visits among clinicians; this is unsurprising given that GPs made up the majority of clinicians included in the France LPD. Similar findings were reported in the ACTION-FRANCE survey of HCPs and people with obesity, which found that weight was mainly discussed with GPs and that diet and exercise therapy were the most commonly discussed weight loss interventions; less than 20% of GPs discussed pharmacological treatments for weight loss [35]. This highlights the pivotal role of GPs as the first point of contact for people with overweight or obesity and the potential impact GPs may have on weight management interventions. A survey of HCPs from selected countries in Europe, including France, found that at least 90% of HCPs were most likely to recommend exercise, patient education and nutritional counselling with people to treat obesity. Two-thirds of HCPs (68%) had recommended OMM and 66% of HCPs had recommended bariatric surgery to treat obesity. Confidence to discuss OMM or bariatric surgery was positively associated with a higher level of knowledge, and one-third of HCPs reported lack of knowledge about weight management as a barrier to obesity treatment [36].

Country-level results from this analysis of new overweight/obesity cases supplement the multi-country data of people with any record of overweight or obesity presented elsewhere, which highlighted that only a small proportion of people with overweight and obesity had formal diagnosis codes and BMI recordings in their EMR, which may lead to an underestimation of the impact of overweight and obesity [21]. Furthermore, suboptimal recording of overweight and obesity may result in fewer interventions offered to people with overweight and obesity [37]. According to the findings of an observational study by Ciemins et al. [38], formal obesity diagnosis may be an important step towards engaging people with obesity to lose weight. Additionally, ORC burden was emphasised, with most people with overweight or obesity reporting at least one ORC. Coupled with our country-specific data from people with new diagnoses of overweight or obesity during the study period, the findings of ORC burden and few recorded interventions in the France cohort, it is evident that further scrutiny of obesity management and early interventions is needed.

A relevant aspect of the present study is that it used an EMR database to evaluate the health status of individuals at the time when overweight or obesity is first recorded in routine care, based on BMI measurements and diagnosis codes. Most large-scale studies on obesity and obesity-related complications at the national level have relied either on population-based surveys or administrative claims/registry data. In contrast, our nationwide EMR database combined measured BMI, diagnosis codes and prescriptions for a large, real-world population. This allowed us to address the burden of obesity-related complications at the exact time overweight/obesity is first recorded in EMR in routine care. Overall, our findings underline the complexity of obesity management, and the high ORC burden at first record of overweight or obesity highlights the need for prompt diagnosis and early intervention. Our results also highlight the limited treatment options available in France at the time of the analysis and the lack of a centralised approach to managing people with obesity across healthcare settings and recording their weight loss interventions. With the increasing recognition of obesity as a disease and the availability of new therapies, the level of recording of interventions and treatment landscape is expected to evolve. Therefore, further analyses to explore changes in recording of weight loss interventions in EMR and treatment patterns in the future are warranted. In addition, while the present study characterized the overweight subgroup (BMI 25 to < 30 kg/m²) within the overweight/obesity cohort (Fig. 3a), a dedicated analysis of overweight alone was not feasible because of the challenges of confirming the absence of obesity in routine-care EMR with non-systematic BMI recording; such an analysis could be a valuable direction for future studies with more complete longitudinal BMI data.

The present study has several limitations that should be considered when interpreting the data. Notably, EMRs are not designed to record data for the purpose of healthcare research, but rather for the purpose of continued patient care; it is possible that records are incomplete or contain errors. The France LPD relied on convenience sampling from selected regional catchment areas and, as such, may not be representative of the French population. It is not possible to link patients from the specialty panel and GP panel as a patient may have distinct identification numbers when presenting in each panel, potentially resulting in duplicated records for people who sought primary and secondary care advice. This could complicate the quantification of treatment patterns; however, the overlap between databases was less than 0.5%. ORCs were identified by a combination of diagnosis codes or diagnosis code and medication use for certain ORC. However, we were unable to use this approach consistently for all relevant ORCs as some do not have specific treatments or were not specifically analysed for the purpose of the present study. As a result of the nature of the database it was not possible to determine when ORCs were first recorded and, as such, whether they occurred as a consequence or were the underlying cause of excess weight development. There were zero records of lifestyle interventions and bariatric surgery reported in the France LPD, so pharmacological therapy was the only intervention field with records available for people with obesity or overweight. GLP-1 RAs included in this study were marketed and reimbursed in France only for the treatment of T2D at the time of this study. As mentioned, we did not exclude individuals with T2D from the analysis of pharmacological therapy use and it is most likely that these medications were prescribed in people with T2D primarily to treat hyperglycaemia, but the nature of the data sources used means this cannot be confirmed. As a result of the descriptive nature of this study, it was not designed to make statistical comparisons; thus, observed differences across data should be interpreted with caution and should be interpreted as descriptive and hypothesis-generating rather than causal.

Conclusions

Results from the French cohort of the IMPACT-O study highlight the burden of ORCs in adults at the first record of obesity (BMI ≥ 30 kg/m²), and frequent occurrence of ORCs in adults at the first record of overweight (BMI ≥ 25 kg/m²). This suggests the need for earlier and more intensive treatment for adults with overweight or obesity. There is a need for increased recording of weight loss interventions in centralised EMR to facilitate the integration of obesity treatment data in France, to better support the management of obesity and to inform future policies.

Supplementary Information

Below is the link to the electronic supplementary material.

Author Contribution

David Jacobi has contributed to the interpretation of data for the work and critical revision of the work for important intellectual content. Esther Artime contributed to the conception and design of the work, interpretation of data for the work and drafting and critical revision of the work for important intellectual content. Marine Bertrand contributed to the analysis and interpretation of data for the work and the drafting and critical revision of the work for important intellectual content. Aya Kayali contributed to the design of the work, interpretation of data for the work and critical revision of the work for important intellectual content. Atif Adam contributed to the design of the work, interpretation of data for the work and critical revision of the work for important intellectual content. Anastasia Lampropoulou contributed to the analysis and interpretation of data for the work and the drafting and critical revision of the work for important intellectual content.

Funding

This work was supported by Eli Lilly and Company. The journal’s Rapid Service Fee and Open Access Fee were funded by Eli Lilly and Company.

Data Availability

All data generated or analysed during this study are included in this published article/as supplementary information files.

Declarations

Conflict of Interest

Esther Artime, Marine Bertrand and Aya Kayali are employees and minor shareholders of Eli Lilly and Company. Anastasia Lampropoulou is a former employee and a former minor shareholder of Eli Lilly and Company. David Jacobi has received consulting fees from Eli Lilly and Company, Novo Nordisk and Fitforme, payment or honoraria from Eli Lilly and Company, Novo Nordisk and Amgen and received travel reimbursement from Eli Lilly and Company and Novo Nordisk. Atif Adam has no conflicts of interest to declare.

Ethical Approval

All analyses performed in this study were conducted in accordance with Data Use Agreement terms as specified by the data owners. Reference made to the France LPD is intended to be descriptive of the data asset licensed by IQVIA. For the France database, there was no institutional review board applicable to the usage and dissemination of the results of this study or required registration of the protocol with additional ethics oversight. This study was performed in accordance with the Helsinki Declaration of 1964 and its later amendments.