Skip to main content
PMC home page
Wellcome Open Research logoLink to Wellcome Open Research
. 2024 Aug 19;8:287. Originally published 2023 Jul 6. [Version 4] doi: 10.12688/wellcomeopenres.19498.4

Eligibility for obesity management in Peru: Analysis of National Health Surveys from 2014 to 2022

Antonio Bernabe-Ortiz 1,a, Rodrigo M Carrillo-Larco 2,3
PMCID: PMC11474143  PMID: 39411211

Version Changes

Revised. Amendments from Version 3

We have resized the Figure 1 to increase font size of y-axis for readibility. In addition, we have rephrased the legend of that figure. Now it reads: "Trends over time of the proportion of subjects with eligibility for (A) obesity medication and (B) bariatric surgery (2014-2022)."

Abstract

Background

The prevalence of overweight and obesity has increased fastest in low- and middle-income countries in the last decades. Together with this rising prevalence, pharmacological and surgical interventions for obesity have emerged. How many people need these treatments is unknown. We quantified the prevalence of people in need of pharmacological and surgical treatment for obesity in Peru between 2014 and 2022.

Methods

Repeated cross-sectional analysis of national health surveys in Peru was conducted. Eligibility for pharmacological treatment for obesity was: body mass index (BMI) ≥30 kg/m 2 or BMI ≥27 kg/m 2 alongside type 2 diabetes or hypertension (self-reported). Eligibility for bariatric surgery were BMI ≥40 kg/m 2 or BMI between 35 to 39.9 kg/m 2 linked to weight-related health problems. We used Poisson regressions to identify associated factors with eligibility for obesity management.

Results

Across years, 260,131 people (mean age 44.0 and 54.5% were women) were studied, 66,629 (27.7%; 95% CI: 27.4% - 28.1%) were eligible for obesity medication, and 5,263 (2.5%; 95% CI: 2.4% - 2.6%) were eligible for bariatric surgery. Female sex, older age, higher socioeconomic level and study year were associated with higher probability of eligibility for both obesity medication and bariatric surgery.

Conclusions

Eligibility for obesity management has increased over time in Peru. There is a need to strengthen policies to tackle overweight and obesity in Peru, acknowledging that some individuals may benefit from pharmacological and surgical interventions.

Keywords: adiposity, body mass index, anthropometrics, treatment, Peru

Introduction

There is a rising prevalence of overweight and obesity that is mainly affecting low- and middle-income countries 1 . In the same sense, mean body mass index (BMI) has increased, by 1 kg/m 2 per decade on average in Latin America 2 , with the subsequent increasing prevalence of obesity observed over time in the region 3 . Peru, a country in Latin America, has followed the same trend with increasing mean BMI and rising prevalence of overweight and obesity 3, 4 .

As obesity is a major driver of the burden of chronic diseases, such as type 2 diabetes, even modest weight loss can produce health benefits 5 . As a result, there are previous and current guidelines and position statements addressing obesity management using nonpharmacological and pharmacological treatments, including metabolic surgery 6– 9 . While global guidelines highlight that lifestyle intervention is the cornerstone for treating obesity, when these interventions fail to reach the weight loss target or did not achieve sustainable weight loss, pharmacological interventions are in order 7, 10 , particularly for individuals with health risks 6, 7, 11 . For example, individuals with BMI ≥27 kg/m 2 with at least one obesity-related comorbidity, or people with BMI ≥30 kg/m 2 with or without metabolic consequences, are eligible for obesity medication 6 . Overall, even though there are pharmacological 12 and surgical interventions 13 for weight management, and there are clear guidelines, how many people meet the criteria for these interventions is unknown. This evidence is essential for health systems to understand whether they have the resources to provide pharmacological or surgical interventions for obesity for those who would most benefit from them.

Consequently, this study aimed to determine the prevalence and trends over time of eligibility for obesity medication and bariatric surgery in the general population by using nationally-representative surveys in Peru from 2014 to 2022. Additionally, we explored potential factors associated with such eligibility criteria.

Methods

Study design

Information from Peruvian National Demographic Surveys (ENDES in Spanish) was utilized for analyses. The ENDES is a nationally representative survey conducted yearly in each of the 25 regions of the country. Data was taken from 2014 to 2022, because since 2014, the ENDES has included a health questionnaire with information about hypertension and type 2 diabetes diagnosis. Furthermore, previous rounds of ENDES included only women.

Population and sampling framework

The ENDES follows a bietapic sampling approach. In urban areas, the sampling units were clusters comprising block or groups of blocks with more than 2,000 individuals and an average of 140 households, whereas the secondary sampling units were the households within each of these clusters. However, in rural areas, the primary sampling units were clusters of 500 to 2,000 individuals and the secondary sampling units were the households similar to urban areas 14 .

For this manuscript, data from participants aged ≥18 years, with complete BMI information, computed based on measured weight and height, were included. We excluded pregnant women or those who were breastfeeding at the time of the survey.

Variables definition

Two variables were the outcomes of interest. The first one was eligibility for obesity medication ( i.e., weight loss drugs), whilst the second one was eligibility for bariatric surgery. Eligibility for obesity medication were BMI ≥30 kg/m 2 or BMI ≥27 kg/m 2 with medical problems linked to obesity such as type 2 diabetes or high blood pressure 15 . Eligibility for bariatric surgery was based on the 1991 National Institute of Health guidelines: BMI ≥40 kg/m 2 or BMI between 35 to 39.9 kg/m 2 linked to weight-related health problems such as type 2 diabetes of high blood pressure 7, 16 . This decision was taken to be conservative in our estimates, but also taking into account the updating process this topic is having over time.

Both weight and height, used to estimate BMI, were measured objectively using standardized procedures. However, information about previous diagnosis of type 2 diabetes and high blood pressure levels were evaluated by self-reporting. We decided to use only self-report information because that would reflect the real-world scenario if we were to deliver pharmacological treatment today (i.e., those who are aware of these conditions would receive treatment). We only utilized these two chronic conditions as they were the only ones available in the ENDES.

To describe participants and assess potential factors associated with the outcomes of interest, we also used socio-demographic and geographical variables. We included sex (female versus male); age (categorized as <30, 30–39, 40–49, 50–59, 60–69, and ≥70 years); education level (in years, <7, 7–11, and ≥12, compatible with primary, secondary and superior education); and socioeconomic level, computed using a wealth index based on assets and services that the participant reported having in the household following the DHS program standard methodology 17 , and then split into quintiles. Geographic area (urban versus rural) was also included as well as study year (as numerical variable, but for descriptive purposes it was used as categorical).

Statistical methods

Analyses were conducted using STATA 16 for Windows (StataCorp, College Station, TX, US). Descriptive statistics and estimates were calculated accounting for the complex survey design using sample strata, primary sampling units and weights, including analysis of subpopulation groups if required 18 .

Initially, the description of variables was carried out using mean and standard deviation (SD) for numerical variables, and absolute and relative frequencies for categorical ones. Prevalence of the two outcomes of interest and their respective 95% confidence intervals (95% CI) were also estimated. Comparisons were performed using the Chi-squared test accounting for the survey design with the Rao-Scott second-order correction 19 for categorical variables.

Factors associated with eligibility for obesity medication and bariatric surgery were evaluated using Poisson regression models. Bivariable (crude) models were built using the outcome of interest and each of the potential associated factors, whereas multivariable models were created by including the outcome and the complete list of potential factors ( i.e., exploratory analysis). Those variables with a p-value <0.05 were considered as significant.

Given the interest to assess trends over time of our outcomes of interest, a marginal model was fitted with a specific outcome and study year as the exposure of interest, adjusted for the other variables ( i.e., sex, age, etc.) and then plotted and presented as figures.

Ethics

We did not consider IRB approval mandatory as this is a secondary analysis of anonymous and freely available public data. Information do not reveal personal identifiers, and as a result, this study does not represent an ethical risk for participants. The Instituto Nacional de Estadística e Informática (INEI in Spanish), the Peruvian governmental organization responsible for ENDES data collection every year, requested informed consent from participants prior to the application of the survey.

Data accessibility

Data used in this analysis is freely available in the webpage of the National Institute of Statistics and Informatics ( INEI).

Results

Description of the study population

From 2014 to 2022, out of a total of 328,167 records, 49,326 (15.0%) were excluded as subjects were aged <18 years, 4,003 (1.2%), because they were pregnant or breastfeeding women, and 14,707 (4.5%) because they did not have complete information in the variables of interest ( i.e., BMI, self-report of hypertension and type 2 diabetes). Thus, data from 260,131 (79.3%) individuals were available for analysis, mean age was 44.0 (SD: 16.9) years, 54.7% were females, and 23.8% were from rural areas. Of note, during the study period, overweight ( i.e., BMI ≥25 kg/m 2) increased from 61.2% in 2014 up to 66.8% in 2022 (p<0.001), whereas obesity ( i.e., BMI ≥30 kg/m 2) increased from 20.9% to 27.3% in the same time period (p<0.001).

Eligibility for obesity management

Over the study years and according to our definition, 66,629 (27.7%; 95% CI: 27.4% - 28.1%) subjects were eligible for obesity medication. Such eligibility was more common among females (p<0.001) and among urban dwellers (p<0.001). In addition ( Table 1), eligibility for obesity medication showed an increase with age (p<0.001), with socioeconomic level (p<0.001), and increased from 24.4% in 2014 to 30.8% in 2022 (p<0.001, see Figure 1A).

Figure 1.

Figure 1.

Open in a new tab

Trends over time of the proportion of subjects with eligibility for ( A) obesity medication and ( B) bariatric surgery (2014–2022).

Table 1. Description of the study population by eligibility for obesity medication: analysis accounting for complex survey design.

Eligibility for obesity medication
No (n = 193,502) Yes (n = 66,629) p-value *
Sex <0.001
   Males 90,809 (77.1%) 22,986 (22.9%)
   Females 102,693 (68.3%) 43,643 (31.7%)
Age (categories) <0.001
   < 30 years 61,815 (85.7%) 11,474 (14.3%)
   30 – 39 years 53,138 (73.4%) 19,456 (26.6%)
   40 – 49 years 29,606 (66.7%) 13,943 (33.3%)
   50 – 59 years 19,591 (63.0%) 10,109 (37.0%)
   60 – 69 years 14,652 (62.9%) 7,216 (37.1%)
   70+ years 14,700 (71.8%) 4,431 (28.2%)
Education level <0.001
   < 7 years 52,089 (71.9%) 17,160 (28.1%)
   7 – 11 years 77,917 (71.4%) 27,502 (28.6%)
   12+ years 54,513 (73.1%) 19,918 (26.9%)
Socioeconomic level <0.001
   Very low 45,722 (84.2%) 8,459 (15.8%)
   Low 41,694 (81.7%) 9,038 (18.3%)
   Middle 35,238 (69.0%) 15,577 (31.0%)
   High 33,500 (65.9%) 16,934 (34.1%)
   Very high 37,348 (69.0%) 16,621 (31.0%)
Geographic area <0.001
   Urban 117,825 (68.8%) 51,446 (31.2%)
   Rural 75,677 (83.4%) 15,183 (16.6%)
Study year <0.001
   2014 19,583 (75.6%) 5,733 (24.4%)
   2015 23,753 (75.4%) 6,985 (24.6%)
   2016 22,767 (74.9%) 6,993 (25.1%)
   2017 23,254 (73.4%) 7,421 (26.6%)
   2018 23,607 (71.6%) 8,389 (28.4%)
   2019 23,003 (72.1%) 8,040 (27.9%)
   2020 14,860 (69.9%) 5,911 (30.1%)
   2021 20,833 (68.3%) 8,575 (31.7%)
   2022 21,842 (69.2%) 8,582 (30.8%)
Open in a new tab

Proportions are weighted according to complex survey design.

* P-value was estimated utilizing the Chi-squared test with the Rao-Scott second-order correction.

Eligibility for bariatric surgery was present in 5,263 (2.5%; 95% CI: 2.4% - 2.6%) and was more common among females (p<0.001) and those from urban areas (p<0.001). Eligibility increased with age (p<0.001) and with socioeconomic level (p<0.001, Table 2). Similar to eligibility for obesity medication, eligibility for bariatric surgery increased from 2.0% in 2014 to 3.3% in 2022 (p<0.001, see Figure 1B).

Table 2. Description of the study population by eligibility for bariatric surgery: analysis accounting for complex survey design.

Eligibility for bariatric surgery
No (n = 254,868) Yes (n = 5,263) p-value *
Sex <0.001
   Males 112,508 (98.5%) 1,287 (1.5%)
   Females 142,360 (96.6%) 3,976 (3.4%)
Age (categories) <0.001
   < 30 years 72,630 (99.1%) 659 (0.9%)
   30 – 39 years 71,346 (98.0%) 1,248 (2.0%)
   40 – 49 years 42,420 (96.9%) 1,129 (3.1%)
   50 – 59 years 28,673 (96.1%) 1,027 (3.9%)
   60 – 69 years 21,062 (95.7%) 806 (4.3%)
   70+ years 18,737 (97.4%) 394 (2.6%)
Education level 0.14
   < 7 years 67,846 (97.5%) 1,403 (2.5%)
   7 – 11 years 103,266 (97.4%) 2,153 (2.6%)
   12+ years 72,902 (97.6%) 1,529 (2.4%)
Socioeconomic level <0.001
   Very low 53,692 (99.1%) 489 (0.9%)
   Low 50,263 (99.1%) 469 (0.9%)
   Middle 49,553 (97.0%) 1,262 (3.0%)
   High 48,832 (96.4%) 1,602 (3.6%)
   Very high 52,528 (97.2%) 1,441 (2.8%)
Geographic area <0.001
   Urban 164,804 (97.0%) 4,467 (3.0%)
   Rural 90,064 (99.1%) 796 (0.9%)
Study year <0.001
   2014 24,861 (98.0%) 455 (2.0%)
   2015 30,222 (98.1%) 516 (1.9%)
   2016 29,210 (97.8%) 550 (2.2%)
   2017 30,105 (97.7%) 570 (2.3%)
   2018 31,363 (97.6%) 633 (2.4%)
   2019 30,457 (97.7%) 586 (2.3%)
   2020 20,284 (97.2%) 487 (2.8%)
   2021 28,691 (96.6%) 717 (3.4%)
   2022 29,675 (96.7%) 749 (3.3%)
Open in a new tab

Proportions are weighted according to complex survey design.

* P-value was estimated utilizing the Chi-squared test with the Rao-Scott second-order correction.

Factors independently associated with obesity management

In the multivariable model ( Table 3), female sex, older age, higher socioeconomic level and recentness of study year were associated with higher probability of eligibility for obesity management. Thus, compared to males, females had 36% (95% CI: 33% - 40%) and 123% (99% - 149%) more probability to be eligible for obesity medication and bariatric surgery, respectively. Age was also associated with eligibility for obesity medication and bariatric surgery, reaching the higher probability in the 60–69 group compared to those <30 years. Socioeconomic level showed a rising trend in the probability to be eligible for obesity management, reaching up to an increase of 62% (95% CI: 55% - 70%) for obesity medication and 111% (95% CI: 71% - 159%) for bariatric surgery, both in the very high socioeconomic level compared to those in the very low level. Finally, each additional year was associated with an increase of 4% (95% CI: 3% - 5%) in the eligibility for obesity medication, whereas it was associated with an increase of 8% (95% CI: 4% - 11%) in the eligibility for bariatric surgery.

Table 3. Factors associated with eligibility for obesity medication and bariatric surgery.

Eligibility for obesity medication Eligibility for bariatric surgery
Bivariable model Multivariable model * Bivariable model Multivariable model *
PR (95% CI) PR (95% CI) PR (95% CI) PR (95% CI)
Sex
   Female (vs. male) 1.39 (1.36 – 1.42) 1.36 (1.33 – 1.40) 2.31 (2.07 – 2.58) 2.23 (1.99 – 2.49)
Age (categories)
   < 30 years Reference Reference Reference Reference
   30 – 39 years 1.85 (1.78 – 1.93) 1.83 (1.76 – 1.90) 2.15 (1.80 – 2.58) 2.09 (1.74 – 2.50)
   40 – 49 years 2.32 (2.23 – 2.42) 2.28 (2.19 – 2.37) 3.38 (2.85 – 4.01) 3.25 (2.74 – 3.87)
   50 – 59 years 2.58 (2.48 – 2.68) 2.52 (2.42 – 2.63) 4.23 (3.56 – 5.02) 4.03 (3.37 – 4.82)
   60 – 69 years 2.59 (2.48 – 2.70) 2.56 (2.44 – 2.67) 4.72 (3.95 – 5.65) 4.57 (3.79 – 5.52)
   70+ years 1.97 (1.87 – 2.07) 2.10 (1.99 – 2.22) 2.81 (2.29 – 3.46) 2.83 (2.25 – 3.57)
Education level
   < 7 years Reference Reference Reference Reference
   7 – 11 years 1.02 (0.99 – 1.05) 1.00 (0.97 – 1.03) 1.04 (0.93 – 1.17) 1.01 (0.89 – 1.14)
   12+ years 0.96 (0.93 – 0.99) 0.86 (0.83 – 0.89) 0.93 (0.82 – 1.05) 0.79 (0.69 – 0.91)
Socioeconomic level
   Very low Reference Reference Reference Reference
   Low 1.16 (1.11 – 1.21) 1.05 (0.99 – 1.11) 1.04 (0.85 – 1.27) 0.75 (0.59 – 0.97)
   Middle 1.96 (1.88 – 2.05) 1.47 (1.39 – 1.55) 3.33 (2.81 – 3.94) 1.68 (1.31 – 2.14)
   High 2.16 (2.07 – 2.25) 1.58 (1.49 – 1.67) 3.91 (3.33 – 4.59) 1.86 (1.46 – 2.39)
   Very high 1.97 (1.89 – 2.05) 1.62 (1.55 – 1.70) 3.12 (2.66 – 3.66) 2.11 (1.71 – 2.59)
Geographic area
   Rural (vs. urban) 0.53 (0.52 – 0.55) 0.73 (0.70 – 0.76) 0.29 (0.26 – 0.32) 0.52 (0.44 – 0.61)
Study year
   Per each additional year 1.04 (1.03 – 1.05) 1.03 (1.02 – 1.04) 1.07 (1.05 – 1.09) 1.08 (1.04 – 1.11)
Open in a new tab

* Model adjusted for the listed variables (PR = prevalence ratio; 95% CI: 95% confidence intervals).

Conversely, education level and geographic area were associated with a lower probability of eligibility for obesity management. Thus, those with a higher education level ( i.e., 12+ years of education) had a 14% (95% CI: 11% - 17%) lower probability of eligibility for obesity medication and 21% (95% CI: 9% - 31%) for bariatric surgery. Similarly, those in rural areas had 27% (95% CI: 24% - 30%) and 48% (95% CI: 39% - 56%) lower probabilities of being eligible for obesity medication and bariatric surgery, respectively.

Discussion

Main findings

The prevalence of overweight and obesity has increased in Peru, and so has the eligibility for obesity medication and bariatric surgery. According to our multivariable models, females, older subjects, and those of a higher socioeconomic level had a higher probability to be eligible for obesity medication and bariatric surgery; in contrast, those with higher education and living in rural areas showed a lower probability. Finally, our results also showed that the probability of being eligible for obesity management increased from 2014 to 2022.

Interpretation of results

A review using US guidelines as frameworks recommended participation in high-intensity programs ( i.e., 14 or more counselling sessions) for at least six months. After that, preventing weight regain can be achieved by participating in a one-year weight-loss maintenance program with at least monthly counselling 20 . However, weight reduction and maintenance only using lifestyle changes alone are difficult. Thus, intensive lifestyle and behavioral modification is a difficult treatment strategy regarding adherence with only modest and variable long-term success. Weight loss medications in addition to behavioral-based strategies increase weight loss and reduce the risk of developing co-morbid conditions ( i.e., type 2 diabetes); however, the use of such drugs have been associated with higher rates of side effects 21 . There is a need for a range of treatment options including access to medication and bariatric surgery for those with severe obesity. Discussing the benefits and risks of treatment with patients should always be considered, as the benefits must outweigh the side effects.

The evidence herein provided is essential for Peruvian health system, and perhaps other health systems in Latin America, to understand the potential needs to provide pharmacological and surgical interventions for obesity. This is relevant because according to a previous cohort study in eight large healthcare organizations in the US, weight-loss medications are rarely prescribed (1.3% of the total cohort) to eligible patients 22 . In participants with overweight or obesity, 2.4 mg of semaglutide once weekly plus lifestyle intervention was associated with sustained, clinically relevant reduction in body weight 23 .

Regarding bariatric surgery, despite the increasing rates of obesity in the US and the improved surgery techniques over the last quarter-century, the number of surgeries has only marginally increased from 1993 to 2016 24 . Moreover, a more recent paper in the same setting estimated that, despite the health benefits of bariatric surgery ( i.e., long-term all-cause mortality, life expectancy, incidence of obesity-related conditions) 25, 26 , only 1% of eligible patients for metabolic surgery were treated appropriately in 2018 27 . Regardless of pharmacological or surgical treatment, we would expect the rates to be much lower in Peru (in comparison to the figures presented for the US) 22, 27 . Thus, the gap to provide people with pharmacological treatment for obesity in Peru is expected to be much wider than it is for other noncommunicable diseases ( e.g., hypertension) 28 .

Public health relevance

Peru has a fragmented healthcare system. Overall, the public sector is dependent on the Ministry of Health, whereas the social security system depends on the Ministry of Labor and Employment Promotion 29 . In December 2020, a document was published to provide evidence-based clinical recommendations for surgical management of obesity among adults 30 for those with social insurance. Nevertheless, no document available exists about the use of obesity medication. On the other hand, the Peruvian Ministry of Health (public sector) approved the National Plan to Prevent and Control Overweight and Obesity taking advantage of the COVID-19 context in March 2022 31 . The document focuses on the articulation of strategic interventions to address overweight and obesity, the promotion of interventions for healthy nutrition and physical activity in diverse environments (household, school, university, among others), the increase of coverage and access to healthcare services for individuals with overweight and obesity; and the development of education strategies to promote healthy lifestyles (virtually using mHealth) 21 as well as mechanisms of follow-up. Despite this, specific and individualized strategies to tackle the problem of obesity have not been proposed. Thus, our results fulfill an information gap about the potential need of a more specific obesity management in our population considering both nonpharmacological and pharmacological interventions following strong evidence-base guidelines.

Strengths and limitations

This analysis benefits from utilizing national representative health surveys in Peru. In addition, short-term trends were assessed using data from different continuous years, from 2014 to 2022. However, this study has limitations that deserve discussion. First, causality cannot be established given the cross-sectional nature of the surveys. Second, self-report conditions, mainly hypertension and type 2 diabetes, were used for pharmacological and surgery eligibility. For instance, eligibility may be underestimated as usually individuals are not aware of having chronic conditions. Besides, our results may be also underestimated as the complete list of comorbidities to define eligibility recommended by international guidelines 32, 33 , was not pursued. In addition, new guidelines and recommendations are arising, so this is still a topic with variating definitions. Thus, our findings can be conservative regarding the need of obesity medication and bariatric surgery. There are both scientific and logistic reasons why we chose an “old” definition. Firstly, we used a definition which is consistent with most epidemiological papers similar to ours 34, 35 , allowing comparability and benchmarking to other populations. Secondly, using newer definitions which do not necessarily include comorbidities (i.e., only include BMI thresholds for eligibility purposes), would substantially increase the number of eligible individuals. As we argued before, we aimed to deliver conservative estimates which may be inform policies and lead to realistic interventions. Reporting much higher prevalence estimates would not help in this regard. Thirdly, in a setting with limited resources, anti-obesity medications may be prescribed to those at the highest risks, such as those with comorbidities (consistent with older definitions). Finally, only some sociodemographic and geographical variables were used for describing potential factors associated with eligibility for obesity management. Nevertheless, we still deliver reliable and actionable prevalence estimates, as well as a preliminary characterization of the population who would most likely benefit from pharmacological and surgical interventions for weight loss.

Conclusions

Eligibility for obesity pharmacological management has increased over time in Peru. Eligibility was more common among women, older age, and those in higher socioeconomic level. There is a need to strengthen policies to tackle overweight and obesity in our country, acknowledging that some individuals may benefit from pharmacological and surgical interventions.

Funding Statement

This work was supported by Wellcome [103994, <a href=https://doi.org/10.35802/103994>https://doi.org/10.35802/103994</a>]; 214185, <a href=https://doi.org/10.35802/214185>https://doi.org/10.35802/214185</a>] ; International Training Fellowships to Antonio Bernabe-Ortiz and Rodrigo M. Carrillo-Larco, respectively]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

[version 4; peer review: 3 approved]

Data availability

Data used in this analysis is freely available in the webpage of the National Institute of Statistics and Informatics (INEI) at https://proyectos.inei.gob.pe/microdatos/.

Author roles

Antonio Bernabe-Ortiz: Conceptualization, data curation, formal analysis, investigation, methodology, supervision, validation, writing – original draft preparation; Rodrigo M. Carrillo-Larco: Conceptualization, formal analysis, investigation, methodology, supervision, Writing – Review & Editing. All the authors read, contributed with substantial intellectual content, and approved the version submitted for publication.

References

  • 1. Ng M, Fleming T, Robinson M, et al. : Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2014;384(9945):766–81. 10.1016/S0140-6736(14)60460-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2. NCD Risk Factor Collaboration (NCD-RisC): Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128·9 million children, adolescents, and adults. Lancet. 2017;390(10113):2627–2642. 10.1016/S0140-6736(17)32129-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3. NCD Risk Factor Collaboration (NCD-RisC) - Americas Working Group: Trends in cardiometabolic risk factors in the Americas between 1980 and 2014: a pooled analysis of population-based surveys. Lancet Glob Health. 2020;8(1):e123–e133. 10.1016/S2214-109X(19)30484-X [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4. de Mola CL, Quispe R, Valle GA, et al. : Nutritional transition in children under five years and women of reproductive age: a 15-years trend analysis in Peru. PLoS One. 2014;9(3): e92550. 10.1371/journal.pone.0092550 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5. US Department of Health and Human Services: Managing overweight and obesity in adults: systematic evidence review from the obesity expert panel, 2013. Bethesda, US: National Institutes of Health,2013. Reference Source
  • 6. Apovian CM, Aronne LJ, Bessesen DH, et al. : Pharmacological management of obesity: an endocrine Society clinical practice guideline. J Clin Endocrinol Metab. 2015;100(2):342–62. 10.1210/jc.2014-3415 [DOI] [PubMed] [Google Scholar]
  • 7. Garvey WT, Mechanick JI, Brett EM, et al. : American Association of Clinical Endocrinologists and American College of Endocrinology comprehensive clinical practice guidelines for medical care of patients with obesity. Endocr Pract. 2016;22 Suppl 3:1–203. 10.4158/EP161365.GL [DOI] [PubMed] [Google Scholar]
  • 8. Eisenberg D, Shikora SA, Aarts E, et al. : 2022 American Society of Metabolic and Bariatric Surgery (ASMBS) and International Federation for the Surgery of Obesity and Metabolic Disorders (IFSO) indications for Metabolic and Bariatric Surgery. Obes Surg. 2023;33(1):3–14. 10.1007/s11695-022-06332-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9. Grunvald E, Shah R, Hernaez R, et al. : AGA clinical practice guideline on pharmacological interventions for adults with obesity. Gastroenterology. 2022;163(5):1198–1225. 10.1053/j.gastro.2022.08.045 [DOI] [PubMed] [Google Scholar]
  • 10. Semlitsch T, Stigler FL, Jeitler K, et al. : Management of overweight and obesity in primary care-a systematic overview of international evidence-based guidelines. Obes Rev. 2019;20(9):1218–30. 10.1111/obr.12889 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11. Ryan DH, Kahan S: Guideline recommendations for obesity management. Med Clin North Am. 2018;102(1):49–63. 10.1016/j.mcna.2017.08.006 [DOI] [PubMed] [Google Scholar]
  • 12. Shi Q, Wang Y, Hao Q, et al. : Pharmacotherapy for adults with overweight and obesity: a systematic review and network meta-analysis of randomised controlled trials. Lancet. 2022;399(10321):259–69. 10.1016/S0140-6736(21)01640-8 [DOI] [PubMed] [Google Scholar]
  • 13. Lester ELW, Padwal RS, Birch DW, et al. : The real-world cost-effectiveness of bariatric surgery for the treatment of severe obesity: a cost-utility analysis. CMAJ Open. 2021;9(2):E673–E679. 10.9778/cmajo.20200188 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14. Informática INdEe: Perú: Encuesta Demográfica y de Salud Familiar ENDES 2019. Lima, Perú: INEI,2020. Reference Source
  • 15. Kushner RF: Weight loss strategies for treatment of obesity: lifestyle management and pharmacotherapy. Prog Cardiovasc Dis. 2018;61(2):246–52. 10.1016/j.pcad.2018.06.001 [DOI] [PubMed] [Google Scholar]
  • 16. Arterburn DE, Telem DA, Kushner RF, et al. : Benefits and risks of bariatric surgery in adults: a review. JAMA. 2020;324(9):879–87. 10.1001/jama.2020.12567 [DOI] [PubMed] [Google Scholar]
  • 17. Rutstein SO, Johnson K: The DHS wealth index. DHS comparative reports no. 6. Calverton, Maryland: ORC Macro,2004. Reference Source
  • 18. West BT, Berglund P, Heeringa SG: A closer examination of subpopulation analysis of complex-sample survey data. Stata J. 2008;8(4):520–31. 10.1177/1536867X0800800404 [DOI] [Google Scholar]
  • 19. Rao JNK, Scott AJ: On Chi-squared tests for multiway contingency tables with cell proportions estimated from survey data. Ann Stat. 1984;12(1):46–60. 10.1214/aos/1176346391 [DOI] [Google Scholar]
  • 20. Wadden TA, Tronieri JS, Butryn ML: Lifestyle modification approaches for the treatment of obesity in adults. Am Psychol. 2020;75(2):235–51. 10.1037/amp0000517 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21. LeBlanc ES, Patnode CD, Webber EM, et al. : Behavioral and pharmacotherapy weight loss interventions to prevent obesity-related morbidity and mortality in adults: updated evidence report and systematic review for the US Preventive Services Task Force. JAMA. 2018;320(11):1172–1191. 10.1001/jama.2018.7777 [DOI] [PubMed] [Google Scholar]
  • 22. Saxon DR, Iwamoto SJ, Mettenbrink CJ, et al. : Antiobesity medication use in 2.2 million adults across eight large health care organizations: 2009-2015. Obesity (Silver Spring). 2019;27(12):1975–81. 10.1002/oby.22581 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23. Wilding JPH, Batterham RL, Calanna S, et al. : Once-weekly semaglutide in adults with overweight or obesity. N Engl J Med. 2021;384(11):989–1002. 10.1056/NEJMoa2032183 [DOI] [PubMed] [Google Scholar]
  • 24. Campos GM, Khoraki J, Browning MG, et al. : Changes in utilization of bariatric surgery in the United States From 1993 to 2016. Ann Surg. 2020;271(2):201–9. 10.1097/SLA.0000000000003554 [DOI] [PubMed] [Google Scholar]
  • 25. Carlsson LMS, Sjöholm K, Jacobson P, et al. : Life expectancy after bariatric surgery in the Swedish Obese Subjects study. N Engl J Med. 2020;383(16):1535–43. 10.1056/NEJMoa2002449 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26. Wiggins T, Guidozzi N, Welbourn R, et al. : Association of bariatric surgery with all-cause mortality and incidence of obesity-related disease at a population level: a systematic review and meta-analysis. PLoS Med. 2020;17(7): e1003206. 10.1371/journal.pmed.1003206 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27. English WJ, DeMaria EJ, Hutter MM, et al. : American Society for Metabolic and Bariatric Surgery 2018 estimate of metabolic and bariatric procedures performed in the United States. Surg Obes Relat Dis. 2020;16(4):457–63. 10.1016/j.soard.2019.12.022 [DOI] [PubMed] [Google Scholar]
  • 28. NCD Risk Factor Collaboration (NCD-RisC): Worldwide trends in hypertension prevalence and progress in treatment and control from 1990 to 2019: a pooled analysis of 1201 population-representative studies with 104 million participants. Lancet. 2021;398(10304):957–980. 10.1016/S0140-6736(21)01330-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29. Carrillo-Larco RM, Guzman-Vilca WC, Leon-Velarde F, et al. : Peru - Progress in health and sciences in 200 years of independence. Lancet Reg Health Am. 2022;7: 100148. 10.1016/j.lana.2021.100148 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30. EsSalud: Instituto de Evaluación de Tecnologías en Salud e Investigación: Guía de Práctica Clínica para el Manejo Quirúrgico de la Obesidad en Adultos: Guía en Versión extensa. Lima, Perú: IETSI,2020. Reference Source
  • 31. Ministerio de Salud: Documento Técnico: Plan Nacional de Prevención y Control del Sobrepeso y Obesidad en el Contexto de la COVID-19. Lima, Peru: MINSA,2022. Reference Source [Google Scholar]
  • 32. Eisenberg D, Shikora SA, Aarts E, et al. : 2022 American Society for Metabolic and Bariatric Surgery (ASMBS) and International Federation for the Surgery of Obesity and Metabolic Disorders (IFSO): Indications for Metabolic and Bariatric Surgery. Surg Obes Relat Dis. 2022;18(12):1345–56. 10.1016/j.soard.2022.08.013 [DOI] [PubMed] [Google Scholar]
  • 33. National Institute for Health and Care Excellence: Obesity: identification, assessment and management (CG189). Reference Source [PubMed]
  • 34. Lyu B, Chang AR, Inker LA, et al. : Socioeconomic status and use of obesogenic and anti-obesity medications in the United States: a population-based study. Lancet Reg Health Am. 2022;11: 100249. 10.1016/j.lana.2022.100249 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35. Stafford RS, Radley DC: National trends in antiobesity medication use. Arch Intern Med. 2003;163(9):1046–50. 10.1001/archinte.163.9.1046 [DOI] [PubMed] [Google Scholar]
Wellcome Open Res. 2024 Oct 23. doi: 10.21956/wellcomeopenres.25281.r100732

Reviewer response for version 4

Santiago Rodriguez Lopez 1,2

Wellcome Open Reseach

Review manuscript: ‘Eligibility for obesity management in Peru: Analysis of National Health Surveys from 2014 to 2022’.

Comments to the authors

This work investigates the prevalence and trends over time in eligibility for obesity medication and bariatric surgery in the general population of Peru by using nationally-representative health surveys from 2014 to 2022. The study uses valuable secondary data and the scope is clearly presented. I believe the manuscript would benefit from addressing some issues, mainly related to the way in which results are presented, their contribution, and comparison to the existing evidence, among others.

Specific comments:

Abstract

  • Methods. Please, provide the years of the surveys.

  • Methods. ‘Eligibility for pharmacological treatment for obesity was: body mass index (BMI) ≥30 kg/m 2 or BMI ≥27 kg/m 2 alongside type 2 diabetes or hypertension (self-reported). Eligibility for bariatric surgery were BMI ≥40 kg/m 2 or BMI between 35 to 39.9 kg/m 2 linked to weight-related health problems’. Is not clear what those weight-related problems refer to. Since they represent type2 diabetes or hypertension (as in the case of pharmacological treatment), please, specify this.

  • Conclusions. The authors mention that ‘some individuals’ may benefit from pharmacological and surgical interventions. Are these the ‘Female sex, older age, higher socioeconomic level and study year were associated with higher probability of eligibility for both obesity medication and bariatric surgery’ reported in the results section of the abstract? Please, specify.

Introduction

  • The authors say that ‘lifestyle intervention’ is the cornerstone for treating obesity. Although is not the main focus of this study, I think is important to provide some reference to the macro-level determinants of obesity. Increasing evidence is reflecting the relevance of obesogenic environments that drive the increasing obesity increments in several regions of the world.

Methods

  • ‘For this manuscript, …’. Please, refer to study/work instead of manuscript.

  • ‘We excluded pregnant women or those who were breastfeeding at the time of the survey.’ Hoy many? Were other variables considered for the sample selection? I think you could provide a flowchart describing the sample selection for all surveys.

  • ‘BMI ≥40 kg/m 2 or BMI between 35 to 39.9 kg/m 2 linked to weight-related health problems such as type 2 diabetes of high blood pressure 7,16.’ Do you mean “such as type 2 diabetes OR high blood pressure 7,16”?

  • ‘Bivariable (crude) models were built using the outcome of interest and each of the potential associated factors,..’. I would add the word ‘alternatively’ to the end of this sentence: ‘Bivariable (crude) models were built using the outcome of interest and each of the potential associated factors, alternatively.’

  • It is not clear what is the ‘marginal model’ the authors fitted to assess trends over time for the outcomes. Please, provide further details on this.

Results

  • ‘From 2014 to 2022, out of a total of 328,167 records, 49,326 (15.0%) were excluded as subjects were aged <18 years, 4,003 (1.2%), because they were pregnant or breastfeeding women, and 14,707 (4.5%) because they did not have complete information in the variables of interest (i.e., BMI, self-report of hypertension and type 2 diabetes). Thus, data from 260,131 (79.3%) individuals were available for analysis’. Since you are describing the sample selection here, I would move this paragraph to the methods section (see my comment above on sample selection).

  • Table 1 and 2. Next to the absolute number of participants in each category, please provide the corresponding %.

  • Figure 1A and B. Legends in Y axis reads ‘Proportion of subjects needing obesity treatment’. Actually, it should refer to ‘Proportion of subjects eligible for obesity treatment’.

  • Figure 1A and B. I find these figures somehow redundant with the information provided in tables 1 and 2; I would suggest not to include them. Otherwise, and given the differences in the proportion of subjects eligible for obesity treatment, you could easily merge both figures into one. If you decide to keep them, please provide more information on how trends over time were estimated here.

  • Eligibility for obesity management. The authors describe how the variables are associated with the two outcomes. Given that these variables similarly behave with both obesity mediation and bariatric surgery -leading to a similar description in both paragraphs- I would merge Tables 1 and 2 into one table and group these findings in a simple paragraph. Then, you would have one table for descriptive analysis (including both outcomes) and one for association analysis.

  • Factors independently associated with obesity management. ‘In the multivariable model (Table 3), female sex, older age, higher socioeconomic level and recentness of study year were associated with higher probability of eligibility for obesity management.’ Given that ‘obesity management’ is not an outcome per se, I would refer to both outcomes separately.

  • Factors independently associated with obesity management. ‘Finally, each additional year was associated with an increase of 4% (95% CI: 3% - 5%) in the eligibility for obesity medication, whereas it was associated with an increase of 8% (95% CI: 4% - 11%) in the eligibility for bariatric surgery.’ Please, be aware that for obesity medication in the multivariate model, the increment per year is 3% not 4%.

Discussion

  • Your results for the associations between level of education (a widely used proxy of socioeconomic position) and socioeconomic level with eligibility for obesity medication/bariatric surgery seem to go in opposite directions. Could you provide an explanation for these findings in the discussion?

  • Interpretation of results. ‘A review using US guidelines as frameworks recommended participation in high-intensity programs (i.e., 14 or more counselling sessions) for at least six months. After that, preventing weight regain can be achieved by participating in a one-year weight-loss maintenance program with at least monthly counselling 20.’ The authors start this subsection with this paragraph which is really difficult to follow without a previous context. Could you rephrase it or move this paragraph further in the discussion?    

  • How your findings relate to those in other countries in the region? The reference for comparison seems to be the US, but what about other countries in Latin America?

  • Conclusions. ‘Eligibility for obesity pharmacological management has increased over time in Peru.’ Do you refer to obesity medication? If so, what about bariatric surgery? In the results the authors say that there were also increments over time among the latter (although less steep).

  • Conclusions. ‘There is a need to strengthen policies to tackle overweight and obesity in our country, acknowledging that some individuals may benefit from pharmacological and surgical interventions.’ Which individuals are the authors referring to? Please, be more specific.

Is the work clearly and accurately presented and does it cite the current literature?

Yes

If applicable, is the statistical analysis and its interpretation appropriate?

Yes

Are all the source data underlying the results available to ensure full reproducibility?

Yes

Is the study design appropriate and is the work technically sound?

Yes

Are the conclusions drawn adequately supported by the results?

Yes

Are sufficient details of methods and analysis provided to allow replication by others?

Yes

Reviewer Expertise:

Social epidemiology

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Wellcome Open Res. 2024 Oct 14. doi: 10.21956/wellcomeopenres.25281.r93996

Reviewer response for version 4

Vance Albaugh 1, Michael Kachmar 2

No further comments.

Is the work clearly and accurately presented and does it cite the current literature?

Partly

If applicable, is the statistical analysis and its interpretation appropriate?

I cannot comment. A qualified statistician is required.

Are all the source data underlying the results available to ensure full reproducibility?

Yes

Is the study design appropriate and is the work technically sound?

Partly

Are the conclusions drawn adequately supported by the results?

Yes

Are sufficient details of methods and analysis provided to allow replication by others?

Yes

Reviewer Expertise:

metabolic/bariatric surgery, obesity medicine

We confirm that we have read this submission and believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Wellcome Open Res. 2024 Aug 9. doi: 10.21956/wellcomeopenres.24812.r85856

Reviewer response for version 3

Vance Albaugh 1, Michael Kachmar 2

We have reviewed the revised article and provide approval of the current draft. We do believe the article would be further enhanced if the following points were addressed but it is acceptable in its current format:

  • Figure 1 Legend and Readability: The legend for Figure 1 should be expanded to provide sufficient information so the figure is understandable on its own. Additionally, the y-axis font size should be increased for better readability.

  • We appreciate the authors for their attention to detail and thorough revisions. We believe this has improved the clarity and comprehensiveness of their manuscript and hope they do too.

Is the work clearly and accurately presented and does it cite the current literature?

Partly

If applicable, is the statistical analysis and its interpretation appropriate?

I cannot comment. A qualified statistician is required.

Are all the source data underlying the results available to ensure full reproducibility?

Yes

Is the study design appropriate and is the work technically sound?

Partly

Are the conclusions drawn adequately supported by the results?

Yes

Are sufficient details of methods and analysis provided to allow replication by others?

Yes

Reviewer Expertise:

metabolic/bariatric surgery

We confirm that we have read this submission and believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however we have significant reservations, as outlined above.

Wellcome Open Res. 2024 Aug 9.
Antonio Bernabe-Ortiz 1

Comment: Figure 1 Legend and Readability: The legend for Figure 1 should be expanded to provide sufficient information so the figure is understandable on its own. Additionally, the y-axis font size should be increased for better readability.

Response: Thanks for the comment. We have resized the Figure 1 to increase font size of y-axis. In addition, we have rephrased the legend of that figure. Now it reads: "Trends over time of the proportion of subjects with eligibility for ( A) obesity medication and ( B) bariatric surgery (2014-2022)."

Wellcome Open Res. 2024 Jun 10. doi: 10.21956/wellcomeopenres.24812.r85857

Reviewer response for version 3

Mary O'Kane 1

I managed to read the revised version and response to comments. I am happy to approve.

Is the work clearly and accurately presented and does it cite the current literature?

Yes

If applicable, is the statistical analysis and its interpretation appropriate?

I cannot comment. A qualified statistician is required.

Are all the source data underlying the results available to ensure full reproducibility?

Yes

Is the study design appropriate and is the work technically sound?

Yes

Are the conclusions drawn adequately supported by the results?

Yes

Are sufficient details of methods and analysis provided to allow replication by others?

Yes

Reviewer Expertise:

Nutrition, dietetics, obesity, bariatric surgery, guidelines

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Wellcome Open Res. 2024 May 11. doi: 10.21956/wellcomeopenres.22020.r71898

Reviewer response for version 2

Vance Albaugh 1, Michael Kachmar 2

This is a peer review of an article for the journal Wellcome Open Research entitled, "Eligibility for Obesity Management in Peru: Analysis of National Health Surveys from 2014 to 2022." This is a longitudinal analysis of public health surveys that were administered as part of the Peruvian national demographic survey from the years 2014 to 2022. Prior years were not included because they only included men. The surveys are all self-reported data, and only hypertension and diabetes are collected in terms of chronic diseases. The purpose of the manuscript was to determine the percentage of the population or trends over time of individuals being eligible for either metabolic/bariatric surgery or anti-obesity medications. The eligibility criteria for these that is defined in the manuscript are older criteria, which are no longer used by most professional societies. However, over time the authors note that the prevalence of obesity is worsening in Peru, and as expected the eligibility for bariatric surgery is also increasing. Regression analysis was used to identify variables associated with a higher probability of eligibility for both obesity medications and bariatric surgery which included female sex, older age, and higher socioeconomic level in conclusion the authors state that eligibility for obesity management has improved/increased over time. Similar to other countries, there is a need to strengthen policies to fight this health epidemic. I have a number of concerns with the article, as it is extremely limited in its analysis because of inherent limitations from the database being used. My comments are below numbered.

1. I think it would be important for the authors to note what segment/percentage of the population the survey was completed relative to the entire population of Peru. There's over 32 million people in Peru and this survey essentially captures less than 1% of that population, which is a significant limitation. Additionally, the fact that this is all self-reported data is another limitation, especially when we know that when's people self-report their height and weight they generally overestimate their height and underestimate their body mass index/body weight. The sheer magnitude of the underestimates being provided in this manuscript should be stated and made clearer for the reader.

2. The fact that the demographic surveys only capture self-reported high blood pressure and self-reported diabetes is a tremendous limitation to this study, again grossly underestimating the health risks of these individuals that have taken part in the survey. I think the overall trends make sense, but I have a hard time accepting any estimates from this data as not only the data but the associated diseases with obesity that would qualify individuals for surgery are not captured except for high blood pressure or diabetes. That the authors mention this in the manuscript, but this is a tremendous limitation similar to number one above.

3. The next limitation that I think is significant is that the indications for anti-obesity medicine and bariatric surgery are not the current guidelines for obesity treatment that are endorsed internationally. This is obviously a limitation, and the years being analyzed would have these older indications, but for the purpose of this manuscript – which is to identify trends in eligibility-I would encourage the authors to use these other and more current recommendations (because we know that any numbers from the data are going to be gross underestimates to begin with).

4. Please addend/increase the information that is in the figure legend for figure 1. Essentially it only states that what is shown is "trends over time of eligibility…" for obesity medication and bariatric surgery. Please put sufficient information in the graphic so that it is understandable completely on its own. These graphs are difficult to interpret. The y-axis font is very small and hard to read.

5. While we appreciate the sentiment of this article is to underscore the growing obesity crisis in Latin America, and more specifically Peru. And, we acknowledge your reference (Ng M, Fleming T, Robinson M, et al 2013) suggests a stabilization of the obesity epidemic in some developed countries. The obesity crisis certainly continues to worsen in developed countries of North America[4,5]. We are not certain your opening statement “Although in high-income countries the rise in prevalence of overweight and obesity has reached a plateau” bolsters your main argument further and given it may be factually incorrect suggest revision.

6. Regarding your statement “As a result, guidelines and position statements have been published to address obesity using nonpharmacological and pharmacological treatments, including metabolic surgery:” Your reference regarding bariatric surgery guidelines is dated (Garvey WT, Mechanick JI, Brett EM, et al. 2013). This article provides a comprehensive review and grading of a decades old evidence base for recommendations in the management of obesity. Regarding surgery, it provides evidence both in line with historically accepted guidelines (BMI >35 with obesity associated disease or BMI >40) and evidence which has been incorporated into the most recent internationally accepted guidelines (BMI >30). You base your methodology on the historic indications for surgical intervention. It may be worthwhile to acknowledge that your methods are based on the 1991 guidelines which were recently updated in 2022[2,7].

7. In your results section it may be clearer if you delineate the directionality or the binary outcome that was associated with your findings. For example, the excerpt “In the multivariable model (Table 3), sex, age, socioeconomic level and study year were associated with higher probability of eligibility for obesity management” may be clearer to the reader if written “In the multivariable model (Table 3), female sex, older age, higher socioeconomic level and recentness of study year were associated with higher probability of eligibility for obesity management.” We would suggest similar revision throughout the manuscript for clarity.

8. In your interpretation of results section, you state: “A review using US guidelines as frameworks recommended participation in high-intensity programs (i.e., 14 or more counselling sessions) for at least six months. After that, preventing weight regain can be achieved by participating in a one-year weight-loss maintenance program with at least monthly counselling 18. However, weight reduction and maintenance only using lifestyle changes alone are difficult.” We believe you are trying to set up an argument that intensive lifestyle and behavioral modification is a difficult treatment strategy regarding adherence with only modest and variable long-term success[3]. This may be more eloquently stated for readability.

9. Likewise, in the second paragraph of the interpretation of results, it appears you are building the argument that given the rise in prevalence of obesity in Peru, it is of the utmost importance that consideration for wider use of anti-obesity medications take place. And additionally, anti-obesity medications, such as semaglutide, provide clinically relevant reductions in body mass. However, we believe this arguments clarity is de-railed by sentence structure and the final sentence “Nevertheless, according to this last study, nausea and diarrhea were the most common adverse events with semaglutide, but they were typically transient and mild-to-moderate in severity” which does not appear to further your argument.

10. Regarding strength and limitations, we agree with the statement “our results may be also underestimated …[regarding] eligibility recommended by international guidelines 30,31.” However, we believe the more important understanding is that your results not only underestimate the magnitude regarding the prevalence of obesity with indication for surgical management because of the inclusion of only a few obesity related conditions. But more importantly because the recommendation for minimum BMI has dropped.

11. Finally, we believe your argument - the growing obesity epidemic in Peru requires recognition with pharmacologic and surgical management - would be more intensely supported by the increased magnitude of effect using the updated guidelines - as a greater number of the population is eligible for surgery. Additionally, this argument may be more simply raised examining solely the prevalence of obesity in Peru - without complicating the argument through the stratification of possible patients to pharmacologic and surgical treatment.

12. Overall I would urge the authors to emphasize many of the limitations which are not emphasized adequately in the current manuscript. There is minimal data that is new, and most countries have increasing obesity and are experiencing similar trends to that of industrialized nations, in which obesity prevalence is increasing and obviously as obesity prevalence increases the eligibility for obesity treatments (anti-obesity medication and bariatric surgery) are also increasing in parallel. There is nothing surprising about this, but from a public health perspective it is important to make sure this is known publicly as the burden of obesity and its associated diseases are significant contributors to morbidity, mortality, and cost/expenses not only direct but also indirect expenses for national healthcare systems.

Is the work clearly and accurately presented and does it cite the current literature?

Partly

If applicable, is the statistical analysis and its interpretation appropriate?

I cannot comment. A qualified statistician is required.

Are all the source data underlying the results available to ensure full reproducibility?

Yes

Is the study design appropriate and is the work technically sound?

Partly

Are the conclusions drawn adequately supported by the results?

Yes

Are sufficient details of methods and analysis provided to allow replication by others?

Yes

Reviewer Expertise:

metabolic/bariatric surgery

We confirm that we have read this submission and believe that we have an appropriate level of expertise to state that we do not consider it to be of an acceptable scientific standard, for reasons outlined above.

References

  • 1. : Unmet health needs of uninsured adults in the United States. JAMA .2000;284(16) : 10.1001/jama.284.16.2061 2061-9 10.1001/jama.284.16.2061 [DOI] [PubMed] [Google Scholar]
  • 2. : 2022 American Society of Metabolic and Bariatric Surgery (ASMBS) and International Federation for the Surgery of Obesity and Metabolic Disorders (IFSO) Indications for Metabolic and Bariatric Surgery. Obes Surg .2023;33(1) : 10.1007/s11695-022-06332-1 3-14 10.1007/s11695-022-06332-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3. : Maintenance of Lost Weight and Long-Term Management of Obesity. Med Clin North Am .2018;102(1) : 10.1016/j.mcna.2017.08.012 183-197 10.1016/j.mcna.2017.08.012 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4. : US Obesity Prevalence Surged Over the Past Decade. JAMA .2023;330(16) : 10.1001/jama.2023.19201 1515 10.1001/jama.2023.19201 [DOI] [PubMed] [Google Scholar]
  • 5. : Trends in obesity across Canada from 2005 to 2018: a consecutive cross-sectional population-based study. CMAJ Open .2022;10(2) : 10.9778/cmajo.20210205 E439-E449 10.9778/cmajo.20210205 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6. : Sociodemographic Patterns of Chronic Disease: How the Mid-South Region Compares to the Rest of the Country. Am J Prev Med .2017;52(1S1) : 10.1016/j.amepre.2016.09.004 S31-S39 10.1016/j.amepre.2016.09.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7. : Gastrointestinal Surgery for Severe Obesity. Annals of Internal Medicine .1991;115(12) : 10.7326/0003-4819-115-12-956 956-961 10.7326/0003-4819-115-12-956 [DOI] [PubMed] [Google Scholar]
Wellcome Open Res. 2023 Aug 14. doi: 10.21956/wellcomeopenres.22020.r65097

Reviewer response for version 2

Mary O'Kane 1

Thank you. My comments have been addressed.

Is the work clearly and accurately presented and does it cite the current literature?

Yes

If applicable, is the statistical analysis and its interpretation appropriate?

I cannot comment. A qualified statistician is required.

Are all the source data underlying the results available to ensure full reproducibility?

Yes

Is the study design appropriate and is the work technically sound?

Yes

Are the conclusions drawn adequately supported by the results?

Yes

Are sufficient details of methods and analysis provided to allow replication by others?

Yes

Reviewer Expertise:

Nutrition, dietetics, obesity, bariatric surgery, guidelines

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Wellcome Open Res. 2023 Aug 7. doi: 10.21956/wellcomeopenres.21599.r64129

Reviewer response for version 1

Mary O'Kane 1

I found the article easy to read and follow. I have some comments:

Introduction

  • In the introduction, should this sentence also include surgical interventions: “This evidence is essential for health systems to understand whether they have the resources to provide pharmacological interventions for obesity for those who would most benefit from them”?

Variables definition

  • Was there a reason that only type 2 diabetes and hypertension, along with BMI, were chosen as the eligibility criteria for medication or bariatric surgery, given that national guidelines include a range of comorbidities? For instance: Eisenberg et al., (2023) 1 and NICE CG189 Obesity.

Discussion

Main findings

  • Reference 18 is a review paper by Wadden et al., discussing the US guidelines (not an international guidelines). The paper acknowledges the difficulties in achieving weight maintenance with lifestyle changes alone, and the need for national policy initiatives addressing the environment, access to healthy food, and other areas. Hence, the need for a range of treatment options including access to medication and bariatric surgery for those with severe obesity. It may be helpful to discuss that the benefits and risks of treatment should always be considered, as the benefits may outweigh the side effects.

Interpretation of results

  • I found interesting that those with the “higher socioeconomic level” had a higher probability for eligibility for obesity medication and bariatric surgery, as this contrasts with many developed countries in which obesity is associated with social deprivation.

  • I was not sure about this statement “These results suggest that broader access to bariatric surgery for eligible people may reduce the long-term sequelae and provide population-level benefits derived from weight loss in high-risk populations”. Given the small number eligible, will bariatric surgery provide population-level benefits? Would it be more appropriate for focus on cost benefits discussed by Lester et al.,? 

  • Given that the eligible comorbidities were limited to Type 2 diabetes and hypertension, it is likely that the numbers eligible for obesity medications and bariatric surgery is underestimated. 

Is the work clearly and accurately presented and does it cite the current literature?

Yes

If applicable, is the statistical analysis and its interpretation appropriate?

I cannot comment. A qualified statistician is required.

Are all the source data underlying the results available to ensure full reproducibility?

Yes

Is the study design appropriate and is the work technically sound?

Yes

Are the conclusions drawn adequately supported by the results?

Yes

Are sufficient details of methods and analysis provided to allow replication by others?

Yes

Reviewer Expertise:

Nutrition, dietetics, obesity, bariatric surgery, guidelines

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

References

  • 1. : 2022 American Society of Metabolic and Bariatric Surgery (ASMBS) and International Federation for the Surgery of Obesity and Metabolic Disorders (IFSO) Indications for Metabolic and Bariatric Surgery. Obes Surg .2023;33(1) : 10.1007/s11695-022-06332-1 3-14 10.1007/s11695-022-06332-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
Wellcome Open Res. 2023 Aug 7.
Antonio Bernabe-Ortiz 1

REVIEWER 1 I found the article easy to read and follow. I have some comments:   Introduction In the introduction, should this sentence also include surgical interventions: “This evidence is essential for health systems to understand whether they have the resources to provide pharmacological interventions for obesity for those who would most benefit from them”?

Response: We have included the phrase suggested. Now it reads: “ This evidence is essential for health systems to understand whether they have the resources to provide pharmacological or surgical interventions for obesity for those who would most benefit from them”.  

Variables definition Was there a reason that only type 2 diabetes and hypertension, along with BMI, were chosen as the eligibility criteria for medication or bariatric surgery, given that national guidelines include a range of comorbidities? For instance: Eisenberg et al., (2023) 1  and  NICE CG189 Obesity .

Response: Thanks for pointing out this. We have clarified this in the Variables definition section by adding: “ We only utilized these two chronic conditions as they were the only ones available in the ENDES”. In addition, in the Strengths and limitations section, we have added: "Besides, our results may be also underestimated as the complete list of comorbities to define eligibility recommended by international guidelines (a,b) , was not pursued.”   References:

  1. Eisenberg D, Shikora SA, Aarts E, Aminian A, Angrisani L, Cohen RV, et al. 2022 American Society for Metabolic and Bariatric Surgery (ASMBS) and International Federation for the Surgery of Obesity and Metabolic Disorders (IFSO): Indications for Metabolic and Bariatric Surgery. Surg Obes Relat Dis 2022;18(12):1345-56.

  2. National Institute for Health and Care Excellence. Obesity: identification, assessment and management (CG189). Available at: www.nice.org.uk/guidance/cg189.

Discussion: Main findings Reference 18 is a review paper by Wadden et al., discussing the US guidelines (not an international guideline). The paper acknowledges the difficulties in achieving weight maintenance with lifestyle changes alone, and the need for national policy initiatives addressing the environment, access to healthy food, and other areas. Hence, the need for a range of treatment options including access to medication and bariatric surgery for those with severe obesity. It may be helpful to discuss that the benefits and risks of treatment should always be considered, as the benefits may outweigh the side effects.

Response: We have modified the paragraph according to reviewer suggestions. Now it reads: “ A review using US guidelines as frameworks recommended participation in high-intensity programs (i.e., 14 or more counselling sessions) for at least six months. After that, preventing weight regain can be achieved by participating in a one-year weight-loss maintenance program with at least monthly counselling (a). However, weight reduction and maintenance only using lifestyle changes alone are difficult. Weight loss medications in addition to behavioral-based strategies increase weight loss and reduce the risk of developing co-morbid conditions (i.e., type 2 diabetes); however, the use of such drugs have been associated with higher rates of side effects (b). There is a need for a range of treatment options including access to medication and bariatric surgery for those with severe obesity. Discussing the benefits and risks of treatment with patients should always be considered, as the benefits must outweigh the side effects.”   References:

  1. Wadden TA, Tronieri JS, Butryn ML: Lifestyle modification approaches for the treatment of obesity in adults. Am Psychol. 2020;75(2):235–51. 32052997 10.1037/amp0000517 7027681

  2. LeBlanc ES, Patnode CD, Webber EM, et al.: Behavioral and Pharmacotherapy Weight Loss Interventions to Prevent Obesity-Related Morbidity and Mortality in Adults: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force. JAMA. 2018;320(11):1172–1191. 30326501 10.1001/jama.2018.7777.

  Interpretation of results

  • I found interesting that those with the “higher socioeconomic level” had a higher probability for eligibility for obesity medication and bariatric surgery, as this contrasts with many developed countries in which obesity is associated with social deprivation.

Response:  In Peru, the association between socioeconomic level and obesity markers is related to the nutritional transition. Thus, Peru, is not a developed country but a middle-income country with huge inequalities. For example, a relatively recent manuscript found that education level was associated with a reduction in the prevalence of obesity, whereas socioeconomic level, assessed as wealth index, was a factor positively associated with obesity (a). So, although surprising, that is an expected result.   References:

  1. Cerpa-Arana SK, Rimarachín-Palacios LM, Bernabe-Ortiz A. Association between socioeconomic level and cardiovascular risk in the Peruvian population. Rev Saude Publica 2022;56:91.

 

  • I was not sure about this statement “These results suggest that broader access to bariatric surgery for eligible people may reduce the long-term sequelae and provide population-level benefits derived from weight loss in high-risk populations”. Given the small number eligible, will bariatric surgery provide population-level benefits? Would it be more appropriate for focus on cost benefits discussed by Lester et al.? 

Response: We have deleted that sentence to avoid confusion.  

  • Given that the eligible comorbidities were limited to type 2 diabetes and hypertension, it is likely that the numbers eligible for obesity medications and bariatric surgery is underestimated. 

Response: We have added that as a limitation as explained in a previous comment.

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Data Availability Statement

    Data used in this analysis is freely available in the webpage of the National Institute of Statistics and Informatics ( INEI).

    Data used in this analysis is freely available in the webpage of the National Institute of Statistics and Informatics (INEI) at https://proyectos.inei.gob.pe/microdatos/.

    Articles from Wellcome Open Research are provided here courtesy of The Wellcome Trust

    RESOURCES