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- v.35(4); Oct-Dec 2010

Study on Obesity and Influence of Dietary Factors on the Weight Status of an Adult Population in Jamnagar City of Gujarat: A Cross-Sectional Analytical Study
Bhavin n vadera.
Department of Community Medicine, MP Shah Medical College, Jamnagar, Gujarat, India
Sudha B Yadav
Babusingh s yadav, dipesh v parmar, sumit v unadkat, background:.
Obesity has reached epidemic proportions globally and is a major contributor to the global burden of chronic diseases. Dietary factors are the major modifiable factors through which many of the external forces promoting weight gain act.
Objectives:
The objectives were to find the prevalence of overweight and obesity in the urban population of Jamnagar and to explore the effect of dietary factors on the weight status of the people.
Materials and Methods:
A cross-sectional study was conducted among the adult population of Jamnagar city. Cluster sampling technique was used to select study samples. Data were collected in a prestructured questionnaire by interviewing subjects through house-to-house visits. Data were analyzed in Epi Info and appropriate statistical methods were used.
The prevalence of overweight and obesity was found to be 22.04% and 5.20%, respectively. Overweight was more prevalent in females than males. The prevalence rose with an increase in age up to 60 years. Among dietary factors, the total calorie intake and habit of snacking had a positive association with weight gain (P < 0.05). The mean intake of oil was more and the mean intake of vegetables was less among overweight subjects than nonoverweight subjects (P < 0.05).
Conclusion:
The prevalence of overweight and obesity in the urban population in Jamnagar was found to be 22.04% and 5.20%, respectively. Total calorie intake as well as composition of diet was the important dietary factor affecting weight gain.
Introduction
Obesity is a complex condition, with serious social and psychological dimensions, affecting virtually all ages and socioeconomic groups. Obesity has reached epidemic proportions globally and is a major contributor to the global burden of chronic diseases and disability. India and many other countries in South-East Asia are currently going through the so-called nutrition transition which is associated with a change in the structure of the diet and rapid increase in the prevalence of obesity.( 1 ) Dietary factors strongly influence the energy balance equation and they are major modifiable factors through which many of the external forces promoting weight gain act. With this background, the present study was conducted with following objectives.
The objectives of the study were to find the prevalence of overweight and obesity in an urban population of Jamnagar and to study the impact of dietary factors on the weight status of the people.
Materials and Methods
The present study was a cross-sectional study. The study was carried out in an urban population within Municipal Corporation limits of Jamnagar city of Gujarat state. The study period was between July 2008 and December 2008.
The sample size was decided using the Epi Info 2002 statistical package. At the 95% confidence level, sample size obtained was 852. The sample size was adjusted to allow for nonresponse and other factors that decrease the yield of usable responses. Taking into account these factors, the sample size derived was 980. The response rate in the present study was 97%. So the final sample size in the present study was 903.
Samples were selected using the cluster sampling technique. A sampling frame was prepared by making a list of cumulative populations of all wards of the city based on the total population of each ward as per census 2001. Thirty clusters were selected proportionate to the population size of wards from the list. To accomplish the sample size, it was decided to select 33 subjects from each cluster. The study subjects were interviewed through house-to-house visits. All persons more than 19 years of age who were present in the household at the time of visit were included in the study. Consent of the participants was taken by initially explaining the purpose of the study.
A predesigned and pretested questionnaire was used for data collection. The questionnaire included information regarding sociodemographic characteristics and dietary factors. A 24-h dietary recall method was used to assess the amount of food consumed. The frequency of food consumption was assessed by a food frequency questionnaire. Standing height and weight were measured. Body mass index (BMI) was used to classify the weight status of subjects. It was derived by dividing weight in kilograms divided by the square of the height in meters (kg/m 2 ).( 2 ) The classification of overweight and obesity was done on the basis of recommendations by WHO [ Table 1 ].( 3 )
Classification of adults according to BMI( 3 )

The data entry and analysis were done using the Epi Info 2002 package. Statistical tests applied were the χ 2 test and Z-test.
The prevalence of overweight was found to be 22.04% in the study population and that of obesity was 5.20% [ Table 2 ]. Mean BMI of the study population was 22.87 kg/m 2 .
Distribution of study subjects according to weight status

The prevalence of overweight was higher in females than males. This difference was statistically significant (P < 0.001). The prevalence was increased with the rise in age. It was highest in the age group of 50-60 years after which it declined. This difference was also statistically significant (P < 0.001). In the study population, people with overweight were in a higher percentage in the upper socioeconomic class than the lower socioeconomic class. There was not much difference in the weight status of people living in slum or nonslum area [ Table 3 ]. The difference in the weight status among different socioeconomic classes and residential areas was not statistically significant.
Weight status of study subjects according to sociodemographic variables

On observing the effect of dietary factors, it was found that the prevalence of overweight was higher among those who consumed more than recommended calories than those who were taking recommended or less calories per day. The difference was found to be statistically significant. Snacking was also associated with the overweight status. There were more overweight people among those who were taking snacks than among those who were only taking two meals and breakfast. The association was found to be statistically significant. Though overweight people were more in the group consuming a mix diet than those who were strictly vegetarian, the difference was not statistically significant [ Table 4 ].
Weight status of study subjects according to various dietary factors

In the present study it was observed that dietary constitutes also affect the weight status. Mean oil consumption was very high (than recommended) in both the nonoverweight and overweight groups but it was significantly higher in overweight people. Similarly, vegetable consumption was quite low (than recommended) in both the groups, and it was significantly lower in overweight subjects than nonoverweights. These observations were statistically significant (P < 0.05) [ Table 5 ].
Weight status of study subjects according to per capita consumption of oil and vegetables

The effect of the frequency of consumption of certain foods concerning the weight status was explored. It was found that as the frequency of taking vegetables and fruits increased, the proportion of overweight subjects decreased. The proportion of overweight increased with the increased intake of fried food although this difference was not statistically significant [ Figure 1 ].

Distribution of overweight subjects according to the frequency of food consumption
The frequency of taking food at restaurants and the frequency of intake of fast food had an impact on the prevalence of overweight. The prevalence was higher with higher frequency of eating in restaurants and intake of fast food. However, these observations were not statistically significant [ Figure 2 ].

Distribution of overweight subjects according to the frequency of intake of restaurant food and fast food
The prevalence of overweight and obesity in the urban population of Jamnagar city was found to be 22.04% and 5.20%, respectively. The prevalence of overweight in an urban population of India, as found in National Family Health Survey during 2005-06, was 11.38%.( 4 ) The prevalence of obesity was 2.24% in the same survey. Though the prevalence found in the present study is higher than the national average, it is lower than that of developed countries. National Health and Nutrition Examination Survey US observed the prevalence of overweight to be 66.3% in 2004. General Household Survey in UK found the prevalence to be 61% in 2003.National Health Survey in Australia found the prevalence to be 49% in 2005.( 5 )The higher prevalence of overweight in the present study could be because of imbalance in the diet and faulty food habits prevalent in the region.
Gender is one of the biological factors affecting the weight status. It was observed in the present study that the prevalence of overweight is generally higher in females than males. Findings of studies conducted in India by Gopinath et al .,( 6 ) Gopalan,( 7 ) Mohan et al .,( 8 ) Mishra et al .,( 9 ) Ramchandran et al .,( 10 ) Reddy et al .,( 11 ) Shukla et al .,( 12 ) and recent National Family Health Survey III (2005-06)( 4 ) also revealed a much higher percentage for obesity/overweight in females than in males. In females, extra energy gets converted into fat. This pattern of energy usage, or "nutrient partitioning," in females contributes to further positive energy balance and fat deposition.( 3 ) Due efforts should be undertaken to decrease overweight or obesity in females to make an impact on overall prevalence.
Age is another biological nonmodifiable factor which influences individual′s susceptibility to weight gain and the development of obesity. In the present study, it was found that overweight prevalence increased with the rise in age. It was highest in the age group of 50-60 years after which it declined. The decline in the proportion of overweight in the older age group might be due to the decreased body mass with age which might be a consequence of decreased calorie intake as well as decreased absorption from the gut. The agewise distribution of obese persons observed in NFHS-III (2005-06)( 4 ) among women also revealed an increasing trend of obesity with the age up to 50 years; in men, a similar trend was observed. Other studies carried out in India by Mishra et al . in 2001( 9 ) and Nutrition Foundation of India in 1998( 13 ) found a similar trend in their observations. Though higher prevalence is observed in the later part of life, this is a consequence of the presence of risk factors of obesity in earlier age. So despite the higher prevalence in the older age group, obesity preventive intervention should be directed in the younger age group and therapeutic and complication prevention interventions should be carried out in later age groups to mitigate the impact of obesity.
Studies have repeatedly shown that the high socioeconomic status is negatively correlated with obesity in developed countries, but positively correlated with it in populations of developing countries.( 14 , 15 ) In the present study, overweight status had a positive association with the socioeconomic level but the association was not statistically significant.
Dietary energy intake is one end of the energy balance equation. The intake of calories more than our body requirement leads to positive energy balance and so obesity. This fact was confirmed in the present study. It was found that the prevalence of overweight was higher among those who consumed more than recommended calories than those who were taking recommended or less calories per day. The difference was found to be statistically significant (P < 0.001). Recent data from Australia, the United States, and Europe further confirm that the increased self-reported energy intake associated with obesity.( 16 )
Among other factors in dietary consumption, the intake of snacks impacted overweight positively while the type of food either vegetarian or mixed did not affect the weight status of subjects significantly.
The average intake of oil and vegetables by the study subjects was far less than the recommended intake of these food items. Also, there was a difference in the amount of consumption of these foods in overweight and nonoverweight groups. The amount of oil intake was more among overweight than nonoverweight subjects and the mean intake of vegetables was less among the overweight subjects than their nonoverweight counterparts. Thus, there was positive association between oil intake and overweight status and a negative association between vegetable intake and overweight status which was statistically significant. Similar findings were observed in the study of Nutrition Foundation of India (1998) which indicated that the consumption of refined oil and saturated fats (ghee and vanaspati) was significantly higher among the obese individuals (P < 0.05).( 13 ) Lin BH et al . (2002), on examining the relationship between fruits and vegetables and obesity, found the negative correlation between vegetable consumption and BMI to be significant among adults.( 17 )
In the present study, an attempt was made to explore the relationship between the frequency of various foods and weight status of subjects. It was observed that overweight was more prevalent among those who were consuming fruits and vegetables less frequently and those who were consuming fried food more frequently though the difference found was not statistically significant. Ledikwe et al . (2006) in their study in US adults found that persons with a high fruit and vegetable intake hadthe lowest obesity prevalence.( 18 ) In exploring the effects of eating habits on body weight, researchers with USDA's economic research service found difference in servings of fruits eaten by healthy weight people, overweight people, and obese. Fruit consumption was found to have a significant negative relationship with the body weight status in all age groups in men and women.( 17 ) In a cross-sectional study among Spanish personsaged 29-69 years, it was found that “fried food” was positively associated with generaland central obesity among subjects in the highest quintileof energy intake from fried food.( 19 ) In a study among middle aged (≥30 years) Bengali Hindu men of Calcutta, it was found that, of the food pattern variables, the frequency of fried snacks consumption was positively and significantly related with central obesity.( 20 )
The effect of higher intake of restaurant food and fast food on weight status was also observed. It was found that the proportion of overweight was more among those subjects who were consuming restaurant food and fast food more frequently. According to the WHO expert committee, high intake of energy-dense micronutrient-poor foods which is the case in most of fast food is convincingly related with unhealthy weight gain and there is a possible relation between the high proportion of intake of food prepared outside home and unhealthy weight gain.( 21 )
The prevalence of overweight and obesity in the urban population of Jamnagar was found to be 22.04% and 5.20%, respectively. Among dietary factors, not only the total calorie intake but also the pattern of food consumption affects the weight status of people. Both the amount and frequency of consumption of various foods influence the weight pattern.
Acknowledgments
We acknowledge cooperation of all the individuals who participated in the study.
Source of Support: Nil
Conflict of Interest: None declared.

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Obesity Research
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Over the years, NHLBI-supported research on overweight and obesity has led to the development of evidence-based prevention and treatment guidelines for healthcare providers. NHLBI research has also led to guidance on how to choose a behavioral weight loss program.
Studies show that the skills learned and support offered by these programs can help most people make the necessary lifestyle changes for weight loss and reduce their risk of serious health conditions such as heart disease and diabetes.
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NHLBI research that really made a difference
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- The NHLBI and other NIH Institutes funded the Obesity-Related Behavioral Intervention Trials (ORBIT) projects , which led to the ORBIT model for developing behavioral treatments to prevent or manage chronic diseases. These studies included families and a variety of demographic groups. A key finding from one study focuses on the importance of targeting psychological factors in obesity treatment.
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The Division of Cardiovascular Sciences , which includes the Clinical Applications and Prevention Branch, funds research to understand how obesity relates to heart disease. The Center for Translation Research and Implementation Science supports the translation and implementation of research, including obesity research, into clinical practice. The Division of Lung Diseases and its National Center on Sleep Disorders Research fund research on the impact of obesity on sleep-disordered breathing.
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Read how African Americans are learning to transform soul food into healthy, delicious meals to prevent cardiovascular disease: Vegan soul food: Will it help fight heart disease, obesity?
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Home > Books > Role of Obesity in Human Health and Disease
Top 100 Most Cited Studies in Obesity Research: A Bibliometric Analysis
Submitted: 07 June 2021 Reviewed: 14 June 2021 Published: 22 December 2021
DOI: 10.5772/intechopen.98877
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Obesity represents a major global public health problem. In the past few decades the prevalence of obesity has increased worldwide. In 2016, an estimated 1.9 billion adults were overweight; of these more than 650 million were obese. There is an urgent need for potential solutions and deeper understanding of the risk factors responsible for obesity. A bibliometric analysis study was designed to provide a comprehensive overview of top 100 most cited studies on obesity indexed in Web of Science database. The online search was conducted on June 6, 2021 using the keywords “Obesity” OR “Obese” OR “Overweight” in title filed with no limitations on document types or languages. The top 100 cited studies were selected in descending order based on number of citations. The obtained data were imported in to Microsoft Excel 2019 to extract the basic information such as title, authors name, journal name, year of publication and total citations. In addition, the data were also imported in to HistCite™ for further citation analysis, and VOSviewer software for windows to plot the data for network visualization mapping. The initial search retrieved a total of 167,553 documents on obesity. Of the total retrieved documents, only top 100 most cited studies on obesity were included for further analysis. These studies were published from 1982 to 2017 in English language. Most of the studies were published as an article (n = 84). The highly cited study on obesity was “Establishing a standard definition for child overweight and obesity worldwide: international survey” published in BMJ-British Medical Journal (Impact Factor 39.890, Incites Journal Citation Reports, 2021) in 2000 cited 10,543 times. The average number of citations per study was 2,947.22 (ranging from 1,566 to 10,543 citations). Two studies had more than 10,000 citations. A total of 2,272 authors from 111 countries were involved. The most prolific author was Flegal KM authored 14 studies with 53,558 citations. The highly active country in obesity research was United States of America. The included studies were published in 33 journals. The most attractive journal was JAMA-Journal of the American Medical Association (Impact Factor 56.272) published 17 studies and cited globally 51,853 times. The most frequently used keywords were obesity (n = 87) and overweight (n = 22). The countries with highest total link strength was United States of America (n = 155), followed by England (n = 140), and Scotland (n = 130). Our results show that most number of highly cited studies were published in developed countries. The findings of this study can serve as a standard benchmark for researchers to provide the quality bibliographic references and insights into the future research trends and scientific cooperation in obesity research.
- bibliometric analysis
Author Information
Tauseef ahmad *.
- Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China
*Address all correspondence to: [email protected];, [email protected]
1. Introduction
Obesity represents a major public health challenge, in the past few decades the prevalence of obesity has increased worldwide and associated with serious adverse health outcomes [ 1 , 2 ]. According to the statistics of World Health Organization, in 2016, an estimated 1.9 billion adults (18 years and older) were overweight, of these more than 650 million were obese. In 2019, 38 million children (under age of 5 years) were overweight or obese [ 3 ].
Obesity associated comorbidities including certain cancer, depression, fatty liver disease, hepatic steatosis, hyperlipidemia, hypertension, obstructive sleep apnea, orthopedic conditions, type 2 diabetes mellitus and social isolation [ 1 , 4 , 5 ]. There is an urgent need for potential solutions and deeper understanding of the risk factors responsible for obesity.
Bibliometric type studies are of great interest, conducted not only to present an overall overview of the published scientific literature but also critical and subjective summarization of the most influential scientific studies [ 6 , 7 , 8 ].
This study aimed to provide a comprehensive overview of top 100 most cited studies on obesity. The finding can serve as a standard benchmark for researchers and to provide the quality bibliographic references.
3.1 Study design
Bibliometric citation analysis study.
3.2 Searching strategy and database
On June 6, 2021 the online search was conducted on Web of Science, Core Collection database (Philadelphia, Pennsylvania, United State of America). The search keywords used were “Obesity” OR “Obese” OR “Overweight” in title filed with no limitations on documents types or languages. The top 100 cited studies were selected in descending order based on number of citations.
3.3 Data extraction
The obtained studies were imported in to Microsoft Excel 2019 to extract the basic information such as title, authors name, journal name, year of publication and total citations. In addition, the downloaded dataset were imported in to HistCite™ for further citation analysis.
3.4 Visualization network
Visualization network co-authorship countries and co-occurrence all keywords were plotted by using VOSviewer software version 1.6.15 ( https://www.vosviewer.com/ ) for windows.
4. Ethical approval
This study did not involve any human or animal subjects, thus, ethical approval was not required.
The initial search retrieved a total of 167,553 documents on obesity indexed in Web of Science database. Of the total retrieved documents, only top 100 most studies on obesity were included in this study. The included studies were published in English language. Most of the studies were published as an article (n = 84) followed by review (n = 14) and letter (n = 1). The average number of citations per study was 2,947.22, ranging from 1,566 to 10,543 citations.
The most cited study on obesity was “Establishing a standard definition for child overweight and obesity worldwide: international survey” published in BMJ-British Medical Journal in 2000 cited 10,543 times. Another study “Positional cloning of the mouse obese gene and its human homolog” published in Nature in 1994 was cited 10,214 times. A total of 10 studies were cited more than 5,000 times. Furthermore, 52 studies were cited at least 2,000 times, while the remaining studies were cited more than 1,500 times. The top 100 studies on obesity is presented in Table 1 .
5.1 Most prolific authors
A total of 2,272 authors contributed to top 100 most cited studies. The most prolific author was Flegal KM authored 14 studies with 53,558 citations, followed by followed by Carroll MD (n = 10, citations = 36,950), and Ogden CL (n = 9, citations = 34,784). Only nine authors authored at least five studies as shown in Table 2 . In addition, only 22 authors contributed in at least three studies.
Top 100 most cited studies on obesity.
Note: LCS: Local citation score; LCS/t: Local citation score per year; GCS: Global citation score; GCS/t: Global citation score per year.
Authors with at least 4 studies.
5.2 Most active countries
A total 111 countries were involved in top 100 most cited studies on obesity. The most active country was United States of America (studies contributed: 75, citations: 217,788), followed by United Kingdom (studies contributed: 18, citations: 57,015), Canada (studies contributed: 9, citations: 17,920), Japan (studies contributed: 9, citations: 26,695), France (studies contributed: 8, citations: 21,228), Sweden (studies contributed: 8, citations: 20,632), and Netherlands (studies contributed: 7, citations: 13,018) as shown in Table 3 . Only 21 countries were involved at least in four studies.
Country with at least 3 studies.
Note: LCS: Local citation score; GCS: Global citation score.
5.3 Journals
The top 100 most cited studies were published in 33 journals. The most attractive journal was JAMA-Journal of the American Medical Association published 17 studies and cited globally 51,853 times as shown in Table 4 . Only seven journals published at least 4 studies, six journals published two studies each, while the remaining journals published a single study each.
Journals published at least 4 studies.
Note: IF: Impact Factor, Incites Journal Citation Reports, 2021; Q: Quartile; LCS: Local citation score; LCS/t: Local citation score per year; GCS: Global citation score; GCS/t: Global citation score per year.
5.4 Commonly used keywords
A total of 366 keywords were used in the top 100 most cited studies. The most widely used keywords were obesity (n = 87) and overweight (n = 22) as shown in Table 5 .
The keywords used at least ten times.
5.5 Year of publication
The top 100 most cited on obesity were published from 1982 to 2017 as shown in Figure 1 . The highest number of studies were published in 2006 (n = 9, citations = 29,552) and 2007 (n = 7, citations = 19,035) as presented in Figures 1 and 2 .

Publication years of top 100 most cited studies in obesity research.

Total global citation score per year of top 100 most cited studies in obesity research.
5.6 Co-authorship countries network visualization
The minimum number of studies for a country was fixed at 3. Of the total countries, only 38 countries were plotted based on total link strength (TLS) as shown in Figure 3 . The countries with highest TLS were United States of America (155), England (140), and Scotland (130).

Co-authorship countries network visualization. Two clusters are formed; red color represents cluster 1 (24 items), and green color represents cluster 2 (14 items).
5.7 Co-occurrence all keywords network visualization
Of the total keywords, only 69 were plotted as shown in Figure 4 . The keyword body-mass index has the highest TLS 117, followed by overweight (65), adipose-tissue (56), prevalence (53), weight (52), and obesity (49).

Co-occurrence all keywords network visualization. Three clusters are formed; red color represents cluster 1 (29 items), green color represents cluster 2 (26 items), and blue color represents cluster 3 (14 items).
6. Discussion
In recent years, bibliometric type studies have been increased significantly, these studies not only recognize the most influential studies in certain area but also determine the research shift and other important insights into the bibliometric parameters. Globally, obesity is a major public health problem and the prevalence has increased in the past few decades. Therefore, this study was undertaken to recognize the most influential studies in obesity research and provide essential bibliographic information. To the best of our knowledge this is the first bibliometric analysis on top 100 most cited studies on obesity indexed in Web of Science database. The highly cited study in obesity research received a total of 10,543 citations. The study published in a highly rated journal in medicine had an impact factor of 39.890 and placed in quartile 1 (Q1) category. The study entitled “Establishing a standard definition for child overweight and obesity worldwide: international survey” provides cut off points for body mass index in childhood of six large nationally representative cross sectional growth studies [ 9 ].
Another study received a total of 10,218 citations. The study titled “Positional cloning of the mouse obese gene and its human homologue” discusses the potential role of obese gene and these genes may function as part of a signaling pathway from adipose tissue that acts to regulate the size of the body fat depot [ 10 ].
The top 100 most cited were published in 33 journals. The most attractive and core journals in obesity research were JAMA-Journal of the American Medical Association (n = 17), and Nature (n = 14) had an impact factor of 56.272, and 49.962 respectively. A total of 31 studies were published in these two journals with a total citations of 100,377, thus representing the quality of work and aiming of the authors for high impact factor journals. Influential studies on obesity were published in higher impact factor journals. Furthermore, studies published in higher impact factor journals are more likely to be cited by the scientific community. The impact factor shows importance and quality of a journal [ 109 ]. The top three authors based on number of studies in obesity research were Flegal KM (n = 14, citations = 53,558), followed by Carroll MD (n = 10, citations = 36,950), and Ogden CL (n = 9, citations = 34,784). In our study, the leading country was United States of America contributed in a total of 75 studies with a total citations of 217,788. The finding is in line with studies in other research areas [ 110 , 111 , 112 , 113 ].
7. Conclusion
This study provides a comprehensive information of the most cited studies in obesity research. Majority of the most cited studies were published by developed countries in higher impact factor journals. The current study might be helpful to researchers for insights into the future research trends and scientific cooperation.
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Burden of disease study of overweight and obesity; the societal impact in terms of cost-of-illness and health-related quality of life
- J. Hecker 1 , 2 ,
- K. Freijer 3 ,
- M. Hiligsmann 2 &
- S. M. A. A. Evers 2 , 4
BMC Public Health volume 22 , Article number: 46 ( 2022 ) Cite this article
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Little is known about the burden that overweight and obesity impose on Dutch society. The aim of this study is to examine this burden in terms of cost-of-illness and health-related quality of life.
A bottom-up, prevalence-based burden of disease study from a societal perspective was performed. Cost-of-illness information including healthcare costs, patient and family costs, and other costs was obtained via the Treatment Inventory of Costs in Patients with psychiatric disorders (TiC-P) questionnaire. Health-related quality of life was assessed through the EuroQol (EQ-5D-5L) and the BODY-Q instruments. Non-parametric bootstrapping was applied to test for significant differences in costs. Subgroup analyses were performed on all outcomes.
A total of 97 people with overweight and obesity completed the survey. Per respondent, mean healthcare costs were €2907, patient and family costs were €4037, and other costs were €4519, leading to a total societal cost of €11,463 per respondent per year. Total costs were significantly higher for respondents with obesity versus overweight and between low & intermediate versus highly educated respondents. The mean utility score of our population was 0.81. A significantly lower utility score was found for respondents with obesity in comparison with respondents with overweight. BODY-Q results show that respondents with obesity scored a significantly lower Rasch-score than did respondents with overweight in three scales. Respondents with a high education level and having paid work scored significantly higher Rasch-scores in two scales than did those with a low education level and without having paid work. The age group 19–29 have significantly higher Rasch-scores in three scales than respondents in the other two age categories.
Conclusions
Overweight and obesity have a considerable impact on the societal costs and on health-related quality of life. The results show that the impact of overweight and obesity go beyond the healthcare sector, as the other costs have the biggest share of the total costs. Another interesting finding of this study is that obesity leads to significant higher costs and lower health-related quality of life than overweight. These findings draw attention to policy making, as collective prevention and effective treatment are needed to reduce this burden.
Peer Review reports
Globally, the prevalence of overweight (defined as body mass index (BMI) ≥ 25 kg/m 2 ) and obesity (defined as BMI ≥ 30 kg/m 2 ) among adults aged 18 years and older has been rising over the past few decades [ 1 ]. Between 1975 and 2016 the prevalence of obesity has nearly tripled worldwide [ 1 ]. In 2016 there were 1.9 billion adults with overweight; of these, 650 million adults were suffering from obesity [ 1 ]. In 2020, 50% of Dutch adults were overweight, of whom 13.9% were suffering from obesity [ 2 ]. The American Medical Association (AMA), the European Centre for Disease Prevention and Control (ECDC), and the European Commission have recognized obesity as a non-communicable disease with several pathophysiological aspects, such as diabetes mellitus and hypertension. These aspects require a range of interventions to advance the treatment and prevention of obesity [ 3 , 4 ]. Obesity can be ranked in multiple groups; a BMI between 30.00 and 34.99 kg/m 2 is stated as obesity class one, a BMI between 35.00 and 39.99 kg/m 2 is obesity class 2 and BMI > 40.00 kg/m 2 is obesity class 3 [ 5 ]. Several studies have shown that obesity and overweight are a public health problem, as it is a risk factor for several health issues. First, obesity and overweight can cause physical problems, such as coronary heart disease, diabetes type 2, hypertension and stroke, certain types of cancer, and pulmonary diseases [ 1 , 6 ]. Secondly, and equally important, obesity and overweight can cause psychological problems, such as depression, stress and anxiety [ 7 , 8 ]. In addition, obesity increases the risk of severe illness or death from the COVID-19 virus [ 9 ]. Moreover, obesity causes societal and economic burdens. The unhealthy years due to sickness and limitations as a result of obesity have a rising impact on societal costs. These include healthcare costs, patient and family costs, and other costs, such as productivity losses [ 10 , 11 , 12 ]. According to Neovius et al., (2012) productivity losses are almost twice as high for people with obesity in comparison with people with healthy weight (defined as BMI > 18.5 and < 25 kg/m 2 ) over a lifetime. Furthermore, research from the Organization for Economic Cooperation and Development (OECD) shows an estimated cost of 172 Euros per capita for treating high BMI (≥ 25 kg/m 2 ) and associated conditions in the OECD countries [ 13 ]. In addition, available data from multiple countries show that the costs attributable to obesity represent 5.5 to 7.8% of total healthcare expenditures [ 14 ]. Due to the physical and psychological problems, people with obesity are, among other things, hampered in their capacity to perform their daily activities, which has a devastating impact on their health-related quality of life (HRQoL) [ 15 ]. Other studies show that there is a relation between weight loss and improved HRQoL; one main reason for this relation is the reduction of metabolic co-morbidities associated with weight loss, such as diabetes mellitus, hypertension, and cardiovascular disease [ 16 , 17 , 18 ].
Despite the international studies showing that overweight and obesity have significant impact on the individual, the healthcare system and the society, there is no study in the Netherlands that reflects the total burden, including costs and HRQoL, that obesity and overweight have on the society as a whole. Furthermore, there is no study in the Netherlands that makes a comparison between overweight and obesity. Knowledge about these actual costs and the associated burden is needed to highlight the importance of the problem for policy and research agendas, and thereby stimulate collective prevention and treatment programs [ 19 ]. The aim of this study is to examine the societal burden of overweight and obesity on the Dutch population in terms of cost-of-illness (COI) and HRQoL.
Study design and setting
This is a prevalence based, bottom-up, prospective study focusing on the burden of disease expressed in COI (Euros) and HRQoL (utilities and Rasch-scores) from a societal perspective, overall based on the Dutch guidelines for costing studies in the healthcare sector [ 20 ]. The societal perspective is the preferred perspective in health economic evaluation, such as burden of disease [ 21 , 22 ]. The societal perspective means that analyst considers all costs and effects that flow from the intervention, regardless who experiences these [ 23 ].
When information was not present in the Dutch guidelines, such as cost information, other sources were used. A numerical code was assigned to each participant as identification, to ensure anonymity of the questionnaire. The results obtained were available only to the researcher and the supervisors.
Participants
Participants in this study were individuals with overweight or obesity. Inclusion criteria were met when individuals were at least 18 years old and when the respondent’s BMI was equal to or higher than 25 kg/m 2 . Weight and length were asked to respondents, based on this information researchers calculated respondent’s BMI. Participants were recruited in cooperation with Partnerschap Overgewicht Nederland (PON) and the use social media, such as Facebook and overweight/obesity platforms. An informative text was used to inform possible respondents about the background and usefulness of the study and requirements for participation, such as the inclusion criteria. All questionnaires that were finished completely were included in the present study. The volume of the study depended on the willingness of people to participate in the study and fill in the questionnaire. This study is a non-WMO research and is therefore reviewed by the Ethics Review Committee for Health, Medicine and Life Sciences (FHML-REC) of Maastricht University. The FHML-REC has approved the protocol of the study (approval number: FHML/2020/068). All methods were carried out in accordance with relevant guidelines and regulations. An informed consent was obtained from the adult individuals with overweight and obesity who wanted to participate in this study before they filled in the questionnaire.
Measurement and analysis
Cost-of-illness (coi).
The study adopted a societal perspective, which incorporates all costs, regardless who incurs them [ 24 ]. The COI followed three steps: identification, measurement and valuation.
Step I: identification of costs
All costs related to obesity and overweight were included. To calculate the COI different costing categories were identified. The first category is healthcare costs, defined as medical care expenditures for diagnosis, treatment, rehabilitation, and costs related to the purchase of supporting devices. The second category included the patient and family costs, i.e. transportation costs, household expenditures, clothing and informal cares of any kind [ 11 ]. The third category is other costs, such as productivity losses [ 11 , 25 ].
Step II: measurement of costs
Overweight and obesity have a strong mental component; therefore the Treatment Inventory of Costs in Patients with psychiatric disorders (TIC-P) was used to measure costs. To keep the focus of the questionnaire on overweight and obesity and to make it complete, questions about patient and family costs were incorporated into the questionnaire. These questions elicit information about the expenditures related to the respondent’s weight, such as adapted clothing, gym subscription, diet books, parking permit, food, etc.. The TIC-P gave insight into general information, such as BMI, age, gender, and socio-economic status, and the different types of costs, such as healthcare costs, and costs in other sectors, related to obesity and overweight [ 26 ]. In short, the TIC-P related to both somatic and mental health cost items as described in step 1 “identification of costs”. Additional File 1 shows the full questionnaire in Dutch.
Step III: valuation of costs
The costs were gathered and calculated in Euros. The valuation of the costs was based on existing costs and cost information derived from the questionnaire. Existing costs, such as costs of medication and outpatient visits, were taken from the Dutch guidelines for costing studies in the healthcare sector [ 20 ]. In case of missing data, a conservative estimate was used. When cost data was missing the lowest cost price was used. When participants stated that they have had appointments with e.g. the dietician, but did not fill in the amount of appointments, calculations were made based on one appointment. Since the Dutch guidelines used cost prices from the year 2014, inflation was taken into account by valuation of the units. The costs were indexed to the year 2020, using rates from Statistics Netherlands. The unit costs were calculated by multiplying the unit price with the volumes of the resources used [ 20 ]. Two methods are available for calculating productivity losses, namely the Human Capital Approach (HCA) and the Friction Cost Method (FCM). In the Netherlands, the general friction period is 12 weeks [ 20 ]. Following the Dutch guidelines, the FCM method was used. Since there were no participants absent from work longer than the friction period of 12 weeks, the HCA method provide similar estimations. The calculation of the productivity loss is equal to what the employer would have paid if the individual had been working, namely the total time of absenteeism multiplied by the cost per day [ 27 ].
Health-related quality of life (HRQoL)
The HRQoL was measured by means of the standard Dutch version of the five-dimensional, five-level EuroQol (EQ-5D-5L). This method is recommended by the Dutch guidelines [ 20 ]. The EQ-5D-5L contains five dimensions of HRQoL, namely mobility, self-care, daily activities, pain/discomfort and depression/anxiety. Each dimension can be rated according to five scores: 1) no problems, 2) slight problems, 3) moderate problems, 4) severe problems and 5) extreme problems [ 28 ].
Disease-specific quality of life was measured using scales of the BODY-Q, which are related to overweight and obesity. A health-specific questionnaire gives more depth and insight regarding to the quality of life [ 20 ]. The BODY-Q is a Patient-Reported Outcome Measure (PROM), related to obesity and overweight. The BODY-Q is a valid, reliable and internally consistent PROM [ 29 ]. The scales that were used from the BODY-Q are all five related to overweight and obesity, namely social well-being, psychological well-being, body image, physical well-being and sexual well-being. Each statement can be rated to 4 levels ranging from totally disagree to totally agree or from never to always. It is important when answering the questions that respondents keep their body in mind.
The five dimensions of the EQ-5D-5L were summed up into a health state. Utility values can be calculated for these health states. The utility score can be valued between 0 and 1, where 0 indicated death and 1 full health. Utilities corresponding with the measured health states were derived from the Dutch tariffs [ 30 ].
The BODY-Q scales can be scored if at least half of the statements are completed; the mean is imputed when there are missing data. For each scale, a raw score was calculated; this is the sum of the levels ranging from 1 to 4. This raw score was computed and converted to a Rasch transformed score, ranging from 0 (lowest) to 100 (highest). Low Rasch scores indicate a low satisfaction with the outcome, whereas higher scores indicate a better outcome. For example, the scale psychological well-being contains 10 statements. When respondents answer all these statements with “totally agree” (score 4), the raw score will be 40, and the Rasch-score will be 100, meaning the best outcome possible.
Subgroup analyses
Subgroup analyses were performed. These subgroups were based on gender, age, BMI, living situation, level of education and work status. The “Age” subgroup is split into 3 groups, namely 19–29, 30–49, and 50+. In the subgroup “BMI” a distinction was made between overweight (BMI ≥ 25 kg/m 2 ) and obesity (BMI ≥ 30 kg/m 2 ). In the subgroup “Living situation” a distinction was made between living together (meaning married or living with partner), or living alone, meaning respondents were not living with a partner (were not married nor living together), but were single (i.e. divorced, widowed, or other). Furthermore, there are 2 groups in the subgroup “Level of education”, where respondents could have a low level of education (lower vocational education, pre-vocational secondary education) and or intermediate level of education (secondary vocational education, senior secondary general education, pre-university education) – these two levels were in one group - or a high level of education (higher professional education, university education) – the second group. Last, there is a subgroup “Paid work” where respondents either have paid work or do not. The reasons for not having paid work could be that they are unemployed, retired, incapacitated, or other.
As cost data are usually skewed and not normally distributed, we had to take into account nonparametric bootstrapping (1000 replications) for all costs categories. The alpha level was set at 0.05 for all cost analyses. The Shapiro-Wilk test was used to test the normality of the HRQoL outcomes. When data was normally distributed, a parametric test (independent t- test) was computed. When data was not normally distributed, a nonparametric test (Mann-Whitney U ) was computed. A value of p < 0.05 was considered to be a statistically significant difference. Analyses were conducted using SPSS Statistics version 24, except for bootstrapping, which was conducted with Microsoft Office Excel 2016.
Over a time period of 6 months (June – December 2020), 97 individuals filled in the questionnaire. The average age of the population was 43.31 years (SD 13.54) and 79 were female. The average BMI was 33.31 (SD 6.71). Most respondents [ 31 ] were suffering from obesity (17 respondents class 1 and 3; 18 respondents class 2); the other respondents [ 32 ] were suffering from overweight. Sixty-eight respondents indicated that they are married or living with their partner; the remaining respondents indicated that they were living alone. Forty-three respondents had a low level of education or intermediate level of education, and 54 respondents were highly educated. Most respondents (83) worked in paid employment. Respondents’ characteristics are displayed in Table 1 .
Table 2 presents an overview of the societal costs attributable to overweight and obesity, including the different costing categories. Of the respondents, 87.6% indicated that they made use of a healthcare service, this also included the use of medication or the purchase of a medical supporting device. For the whole study population the average healthcare costs per 6 months were €1453.62 (SD 3512.93). Additional File 2 provides an overview of the costing prices for the various healthcare services. Additional Files 3 and 4 show a list of all medication, both prescribed and over the counter, used by respondents.
The average patient and family costs per 6 months were €2018.34 (SD 2538.53). Attempts at weight loss included several methods, including gym subscription, diet books, personal training, adapted diet et cetera. Thirty-four per cent of the respondents indicated that they were absent from work in the past 6 months due to sickness, and 37.1% of respondents indicated that they had physical and/or mental complaints while being present at work. This caused presenteeism. This leads to an average of total other costs of €2259.37 (SD 6141.23). The total societal costs per individual suffering from overweight or obesity in this study are €5731.33 (SD 8238.70) per 6 months, corresponding to €11,462.66 per year.
The mean utility of the study population was 0.81 (SD 0.18). The dimension pain/discomfort is slightly affected, with 40.2% having minor problems, 16.5% having moderate problems, and a median of score 2 (minor problems). The majority of the respondents indicated that there were no or minor problems for the other dimensions, shown in Table 3 .
Table 4 shows the BODY-Q Rasch-scores for each of the HRQoL scales. The scale “Body image” scored the lowest Rasch-score (mean of 36.37), meaning a lower satisfaction with the outcome.
Subgroup analysis
Cost of illness (coi).
A subgroup analysis was performed for all relevant subgroups, based on gender, age, BMI, living situation, level of education and work status. As our costs were highly skewed, the normality assumption was violated. Therefore, bootstrapping was performed on all subgroups (Fig. 1 ). Additional Files 5 , 6 , 7 , 8 show the results in more detail. Bootstrapped results showed that the other costs and total societal costs were significantly higher for respondents suffering from obesity in comparison to respondents with overweight. Furthermore, other costs and total societal costs were significantly higher for respondents with low and intermediate education in comparison with highly educated respondents.

Bootstrapped subgroup analysis Cost-of-Illness (COI). *If CI includes 0, no significant difference is found. **Significant difference in costs between groups in subgroup
A subgroup analysis for the utility scores, derived from the EQ-5D-5L, was performed. The utility scores were not normally distributed. The Mann-Whitney U test was performed to test for significant differences ( p < 0.05). Significant lower utility scores were found for respondents with obesity (0.77) in comparison to respondents with overweight (0.86). In addition, respondents in the age group of 19–29 had a significantly higher utility score (0.87) than did respondents in the other age categories (0.79). Furthermore, respondents who worked in paid employment indicated the lowest mean utility score of 0.71. The results are shown in Fig. 2 . Detailed results are shown in Additional File 9 .

Subgroup analysis of the mean utility score derived from the five-dimensional, five-level EuroQol (EQ-5D-5L). *If p < 0.05, a statistically significant difference is found. **Significant difference in utility score between groups in subgroup. a**Significant difference between age group 19–29 and 30–49 and age group 19–29 and 50+
Results for the subgroup analysis for the BODY-Q are shown in Fig. 3 and in more detail in Additional Files 10 .1–10.5. The scales of psychological well-being, social well-being, and sexual well-being were normally distributed according to the Shapiro-Wilk test. For these scales an independent t -test was used to test for significant differences. The scales of body image and physical well-being were not normally distributed. For these scales the Mann-Whitney U test was performed to test for significant differences ( p < 0.05). The results show that respondents with overweight have a significantly higher Rasch-score than do respondents with obesity in the scales for body image, physical well-being, and sexual well-being. In addition, there is a significant difference in the subgroup “Level of education”; respondents with a low or intermediate level of education have a significantly lower Rasch-score than respondents with higher education in the scales for psychological well-being and social well-being. Furthermore, in the scales for social well-being and sexual well-being, a significant difference is found between respondents who have paid work and those who do not, with a significantly lower Rasch-score in the latter. Last, there are significant differences in the subgroup “Age”. In the scales for body image and sexual well-being, a significantly higher Rasch-score is found for respondents aged 19–29 and 30–49. Also, in the scale for physical well-being, respondents aged 19–29 have a significantly higher Rasch-score in comparison with respondents aged 50 + .

Subgroup analysis of the mean Rasch-scores derived from the BODY-Q. *If p < 0.05, a statistically significant difference is found. **Significant difference in Rasch-scores between groups in subgroup
This study examined the societal burden of overweight and obesity on the Dutch population in terms of COI and HRQoL. Our COI results show that the average societal costs of people with obesity and overweight are €5731.34 per person over the last 6 months, corresponding to €11,462.66 per year. Of these yearly costs, productivity losses make up the biggest share, namely €4518.7, and the healthcare costs have the lowest share, of €2907.24 per person per year, illustrating that the impact of overweight and obesity is significant beyond the healthcare sector. Our HRQoL results show a mean utility score of 0.81 for our population, derived from the EQ-5D-5L. BODY-Q results show the lowest Rasch-score of 36.37 in the scale for “Body image”. The remaining BODY-Q scales have a Rasch-score between 58.69 and 72.93.
In the Netherlands, 50% of the population has a BMI of ≥25 kg/m 2 [ 2 ]. If we extrapolate our costs to national level, the total healthcare expenditure due to overweight and obesity is €1453.62 per capita per year. Other studies show healthcare expenditures of €290.72–€476 per capita per year in the Netherlands [ 13 , 33 ]. Our study indicates that on a national level the productivity losses are €2249.37 per capita. The OECD indicates that the productivity losses are €739.19 per capita per year in the Netherlands [ 13 ]. The higher results for our study are partly due to the differences in the study design of these COI studies, i.e. top-down versus bottom-up.
Results from analysing the results from the subgroups show that in our study obesity was significantly associated with higher costs; respondents with obesity reported higher healthcare costs, patient and family costs, and significantly higher other costs and total societal costs in comparison with respondents with overweight. There are several causes for these higher costs. There are studies that indicate that obesity leads to higher healthcare costs in comparison with overweight, including costs related to diabetes and heart disease [ 34 , 35 , 36 ]. Analysis of the prescribed medication list (shown in Additional File 3 ) shows that our population also uses medication related to diabetes and heart disease. Looking at the productivity losses, studies indicate that a higher BMI is associated with more absenteeism and presenteeism, which is in line with our study. People with obesity or overweight are not only sick more often, but also longer than are people with a healthy weight [ 10 , 37 , 38 , 39 ]. Last, persons with obesity are hampered severely in their day-to-day physical activities [ 15 ]. Our results show that respondents with obesity have higher patient and family costs than respondents with overweight. It is plausible that this result comes from the fact that respondents with obesity are more hampered in their day-to-day physical activities, and need more informal care, than do respondents with overweight.
In addition, level of education was also a significantly associated with higher costs; other costs and total societal costs were significantly higher for respondents with a low or intermediate level of education in comparison with highly educated respondents. Findings of the OECD and the Dutch Central Bureau of Statistics (CBS) indicate that a lower level of education is associated with a higher BMI [ 2 , 40 ]. In our study, highly educated respondents have a slightly higher BMI (33.57) in comparison with respondents with a low or intermediate education (32.99). You could hypothesize that level of education and BMI are not related, but further research is needed to confirm this. Furthermore, our study it shows that respondents with a lower level of education are more often absent from work. Studies show that people with a lower level of education have less knowledge about health, which leads to more disabilities and higher productivity losses, resulting in higher other costs [ 41 , 42 ].
The burden of obesity and overweight on the HRQoL is large if you compare the utility of our population (0.81) with the utility of the Dutch population in general (0.91–0.96), indicating that obesity and overweight carry a high burden for the respondents [ 30 ]. In our study, respondents with obesity indicate a significantly lower utility score (0.77) in comparison with respondents with overweight (0.86). According to Larsson et al. the HRQoL is negatively influenced by a higher level of obesity [ 43 ]. Furthermore, respondents in the age group of 19–29 indicate a significantly higher utility score (0.89) in comparison with the other age categories (0.79). This is in line with other studies, which show increasing problems in all EQ-5D dimensions with age [ 44 , 45 ]. The HRQoL impact was highest on the dimension “Pain/discomfort”. This dimension is directly related to obesity, as people who lose weight report improved physical functioning and decreased bodily pain [ 15 , 46 ]. For the disease-specific quality of life the lowest score is shown in the scale of “Body image”. Several studies show that overweight and obesity are strongly related to body dissatisfaction [ 32 , 47 , 48 ]. Furthermore, it was remarkable that only 74 out of 97 respondents were willing to fill in the questions about sexual well-being. According to Kolotkin et al. obesity is associated with lack of enjoyment and desire for sexual activity. In addition, obesity also leads to difficulties in sexual performance and avoidance of sexual encounters [ 49 ]. These facts could clarify the resistance to fill in these questions.
Strengths and limitations
This study has several strengths. To the best of our knowledge, this is the first study investigating the societal burden of obesity and overweight in the Netherlands, including costs and quality of life. This study distinguishes itself from other studies by including, next to a general quality of life questionnaire, a disease-specific quality of life questionnaire, namely the BODY-Q. Furthermore this study incorporates several costs categories, such as healthcare costs, patient and family costs, and other costs (such as productivity losses). Combining this information leads to a full overview of the total burden overweight and obesity have on the society. This was a prevalence-based, bottom-up study, which means that cost units were collected on an individual level within a specific time period. In comparison to the top-down approach, the bottom-up approach has more informative power [ 50 ]. The prevalence-based approach is more useful than the incidence-based approach when the aim of the study is to draw decision-makers’ interest toward diseases whose burden is underestimated, or when the aim is to plan cost containment policies [ 50 ]. Moreover, the study is from a societal perspective, which means that all costs are taken into account. This is the most comprehensive approach and meets the principal aim of a Burden of Disease study, namely measuring the burden of the disease on society as a whole [ 11 , 50 ]. Last, the EQ-5D-5L is not specific to people who are suffering from overweight and obesity, which makes it less sensitive for disease-specific effects on the quality of life. Therefore, we incorporated the BODY-Q, which makes the HRQoL in this study more specific for individuals with overweight and obesity [ 20 ].
There are some limitations in this study that need to be considered. First, we used retrospective questioning, which can lead to recall bias [ 51 ]. To minimize this bias, a time horizon of 6 months was used, because it gives the researcher the opportunity to collect relevant data and it is an acceptable time frame for participants to fill in the questionnaire with correct information. Furthermore, respondents did not always fill in the questionnaire completely, especially regarding to costs they had, which made it necessary to make an estimation of these costs. This made interpreting the actual costs harder and, therefore, it could be possible that costs are underestimated or overestimated. In addition, the sample size may preclude the use of multivariable analyses and therefore it could be possible that there might be some biases according to gender, age, socio-economic status, comorbidities, pregnancy, and/or menopause. These biases could also arise from the high portion of women relative to men in this study. Because of the small sample size and the high portion of women relative to men, it is also not possible to generalize the results to the whole Dutch population.
Last, in 2019–2020 we lived in the COVID-19 pandemic, which could have an influence on the total costs respondents incurred. In 2020 some non-essential healthcare services were not available. It could be possible that there is an underestimation of the healthcare services used, because individuals simply could not use some of these services. Furthermore, all restaurants were closed during some months in 2020–2021. This could lead to an underestimation of the patient and family costs. Regarding the other costs, it could be possible that respondents were more absent from work due to sickness, because it was not allowed to go to work with a minor cold. However, respondents filled in the questionnaire during June, July and August in 2020, which means that those questionnaires are only slightly affected regarding healthcare costs since only non-essential healthcare services were scaled down for a very short time in May 2020. Regarding patient and family costs, respondents were asked what their average monthly expenses were for dining out and food delivery. With this way of asking, we believe that most respondents did not keep the pandemic in mind and that the outcomes for patient and family costs are not or only slightly affected.
Implications for policy, research and clinical practice
There are some implication for policy and clinical practice. First, more attention should be paid to education about the causes and influencing factors on the existence of overweight and obesity, such as a healthy lifestyle, use of medication with a side effect of increasing weight, social economic, hormonal and/or genetic factors etc. at an early age and on all levels of education [ 52 ]. The existing approach of eating less and moving more as the only solution for solving this condition is really outdated and can harm the patient even more. The impact of overweight and obesity on the HRQoL should not be neglected in treating this disease. Accordingly, it is thus important to consider the involvement of a psychologist in the treatment of overweight and obesity [ 31 ]. Last, this study again shows that overweight and obesity are complex conditions. It is important that people who suffer from overweight and obesity get effective support, such as education regarding to their disease, reimbursed access to care, a healthy workplace, and mental support in overcoming and managing this disease [ 53 ].
Since little research has been done on the burden of overweight and obesity, further research is recommended to increase knowledge on all aspects of this burden. This research should be performed when there is no pandemic. It would be interesting to make a direct comparison with the healthy population and/or other countries in future research. In addition, further exploration of the BODY-Q is needed to make a direct utility comparison with the EQ-5D-5L. Last, the use of the data gathered from this study could be important for economic evaluations in overweight and obesity.
This study indicates that overweight and obesity have a considerable impact on the societal costs and HRQoL in the Netherlands. The results show that the impact of overweight and obesity go well beyond the healthcare sector, as the costs of productivity losses have the biggest share of the total societal costs of this disease. Another interesting finding of this study is that obesity leads to significant higher costs and lower HRQoL than overweight. This impact draws attention to policy making, as collective prevention and effective personalized treatment are needed to reduce this burden.
Availability of data and materials
The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.
Abbreviations
American Medical Association
Body Mass Index
Centraal Bureau voor de Statistiek
Cost of Illness
European Centre for Disease Prevention and Control
Five-dimensional, Five-level EuroQol
Friction cost Method
Ethics Review Committee for Health, Medicine and Life Sciences
Human Capital Approach
Health-related Quality of Life
Organization for Economic Cooperation and Development
Partnerschap Overgewicht Nederland
Treatment Inventory of Costs in Patients with psychiatric disorders
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Acknowledgements
The authors would like to thank the participants, the staff of Partnerschap Overgewicht Nederland (PON), direct partners of PON, and Claire de Vries who invested time in this study by distributing, scoring or filling in the questionnaire. SE and KF are co-founders and members of ISPOR Nutrition Economics Special Interest Group ( https://www.ispor.org/member-groups/special-interest-groups/nutrition-economics ) and of HTAi Interest Group Public Health ( https://htai.org/interest-groups/public-health/ ).
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Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
Department of Health Service Research, Care and Public Health Research Institute (CAPHRI), Maastricht University, PO box 616, 6200, MD, Maastricht, The Netherlands
J. Hecker, M. Hiligsmann & S. M. A. A. Evers
Partnerschap Overgewicht Nederland (PON), Erasmus MC, Rotterdam, The Netherlands
Centre for Economic Evaluation and Machine learning, Netherlands Institute of Mental Health and Addiction, Trimbos Institute, Utrecht, The Netherlands
S. M. A. A. Evers
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Contributions
SE, KF, and JH set up the study design. JH collected the data and interpreted the results. JH wrote the manuscript, with great contribution from SE, KF, and MH. All authors read and approved the final manuscript.
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Ethics approval and consent to participate.
This study is a non-WMO research and is therefore reviewed by the Ethics Review Committee for Health, Medicine and Life Sciences (FHML-REC) of Maastricht University. The FHML-REC has approved the protocol of the study (approval number: FHML/2020/068). All methods were carried out in accordance with relevant guidelines and regulations. An informed consent was obtained from the adult individuals with overweight and obesity who wanted to participate in this study before they filled in the questionnaire.
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Supplementary Information
Additional file 1..
Questionnaire (in Dutch).
Additional file 2.
Costing prices.
Additional file 3.
Prescribed medication list.
Additional file 4.
Over the counter medication list.
Additional file 5.
Subgroup analysis of healthcare costs.
Additional file 6.
Subgroup analysis of patient and family costs.
Additional file 7.
Subgroup analysis of other costs.
Additional file 8.
Subgroup analysis of total societal costs.
Additional file 9.
Subgroup analysis utility score derived from the five-dimensional, five-level EuroQol.
Additional file 10.
Subgroup analysis Rasch-score derived from BODY-Q, scale of psychological well-being. Subgroup analysis Rasch-score derived from BODY-Q, scale of social well-being. Subgroup analysis Rasch-score derived from BODY-Q, scale of body image. Subgroup analysis Rasch-score derived from BODY-Q, scale of physical well-being. Subgroup analysis Rasch-score derived from BODY-Q, scale of sexual well-being.
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Hecker, J., Freijer, K., Hiligsmann, M. et al. Burden of disease study of overweight and obesity; the societal impact in terms of cost-of-illness and health-related quality of life. BMC Public Health 22 , 46 (2022). https://doi.org/10.1186/s12889-021-12449-2
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Published : 07 January 2022
DOI : https://doi.org/10.1186/s12889-021-12449-2
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Specific Aims:
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Vitamin D deficiency has been linked to endothelial dysfunction in adults. Obese adolescents have a high prevalence of Vitamin D deficiency as well as evidence of endothelial dysfunction. Our hypothesis is that supplementation of Vitamin D deficient adolescents with Vitamin D would lead to improvement in endothelial dysfunction.
FIT is grounded in social cognitive, self-determination, and family systems theories and, as such, aims to promote healthy eating and movement habits by facilitating the development of parent-adolescent communication and problem-solving skills to support the adolescents’ and family’s pursuit of health behavior change goals.
The purpose of this study is to examine whether an education program, designed in partnership with teachers at Moreland Elementary School in West St. Paul and Mayo Clinic InSciEd Out scientists, is able to influence the behavior and health literacy of students. This information will be collected in surveys before and after the students are given the curriculum during the school day.
The purpose of this study is to evaluate the impact of a family-based lifestyle program (KidShape 2.0) on BMI and waist circumference of children who are overweight or obese, to evaluate the impact of KidShape 2.0 on BMI and waist circumference of the parent/guardian of participating children, and to evaluate the impact of KidShape 2.0 on knowledge acquisition of the parent/guardian of participating children.
Exendin-(9,39) has been shown to have effects on beta-cell function, and after gastric bypass, to accelerate gastrointestinal transit. - infused at rates of 300pmol/kg/min. Given that gastrointestinal transit is typically delayed by Glucagon-Like Peptide-1 (GLP-1) and also that this hormone causes decreased food intake through increased satiation, it is reasonable to expect an effect of Exendin-9,39 on appetite. This may help explain the effects of gastric bypass on food intake. To examine the effect of Exendin on food intake we propose a dose-response study to determine whether the compound has effects in a dose-dependent fashion. We will examine the presence ...
New studies are revealing how a high-fat diet could be making the cells of the intestinal lining more likely to become cancerous. The purpose of this study is to find how the microbe envntironment of the intestines in obesity influences the growth of intestinal stem cells, which could then trigger intestinal tumors.
The purpose of this study is to increase the measurement of BMI and WC in the overweight (BMI at or greater than the 85th percentile) and obese (BMI at or greater than 95th percentile) outpatient pediatric population ages 6-19 at Mayo Clinic Rochester and surrounding satellite clinics. Educate providers and nursing staff on the importance and technique of measuring the WC in the overweight and obese outpatient pediatric population with at least a yearly WC on every child with a BMI at or greater than the 85th percentile. Determine the prevalence of various components of the metabolic syndrome (MS) including ...
This study will evaluate obesity as a comorbidity in a population of patients with irritable bowel syndrome (IBS), and assess this cohort for vitamin D-deficiency. It will also determine whether alterations in the fecal microbiome and metaproteome, associated with vitamin D deficiency or other factors, underpin obesity-IBS comorbidity.
The objective of this study is to leverage existing social networks for health behavior change relevant to obesity and cardiovascular risk among immigrant populations in Southeast MN.
To determine the accuracy of unguided versus ultrasound (US) guided knee joint injections in obese patients with no clinically detectable effusion.
Opioid medications such as morphine, hydrocodone and oxycodone are standard for treating pain after surgery, however there are disadvantages. Because of the way opioids work, gastric bypass patients may have an increased risk of having sedation or problems with breathing. In patients with sleep apnea, opioids may increase the risk of severe apnea. Ketamine is an alternative pain medicine that can be used to treat pain after surgery and may have fewer effects on breathing. Using ketamine as part of the regimen may be a better choice for laparoscopic gastric bypass patients. This study is being done to find out ...
The purpose of the study is to conduct qualitative interviews of participants in a sleep restriction study who were allowed free snacking to learn about their self-observations regarding their eating motivations and behaviors.
The purpose of this research is to find out if an aggressive intervention to lose weight, will improve symptoms in patients with obesity-related cardiomyopathy, which is also known as the obese phenotype of heart failure with preserved ejection fraction (HFpEF).
This protocol is being conducted to determine the mechanisms responsible for insulin resistance, obesity and type 2 diabetes.
The purpose of this study is to determine through a retrospective cohort if rapid gastric emptying is not only associated with obesity, but if it predicts the future development of the disease.
The purpose of this study is to elicit detailed information from patients diagnosed with a sleep-related breathing disorder with severe obesity and sleep medicine providers regarding attitudes toward and acceptance of a multicomponent weight loss intervention based in health coaching. We anticipate that gaining a deeper understanding of attitudes toward weight loss in this population will provide insight into what may be feasible and acceptable aspects of a weight loss intervention. This information will then help guide the development of a multicomponent weight loss intervention based in health coaching and aimed at decreasing disease burden, increasing PAP adherence, and improving ...
The primary purpose of this study is to investigate the relationship between a technology-assisted diet and exercise program which is easily implemented in an outpatient setting and the levels of biomarkers that have been associated with breast cancer recurrence risk in overweight women with stage 0, I, or II breast cancer.
The purpose of this study is to test the hypothesis that obesity is associated with impairment of cardiovascular reflex control, and that this impairment is linked to deficient leptin activity.
The aim of the study is to investigate the effects of a 3-month resistance exercise program (in people aged 50 to 75) on muscle mass, body composition, muscle strength, brain function and cognition, muscle efficiency processing blood sugar, the body’s ability to build muscle, and fat cells.
Earlier research has shown that exercise has significant benefits in preventing certain diseases and conditions such as diabetes, dementia, heart disease, and more. We also know from other research that resistance exercise (lifting weights) and aerobic exercise (running, biking, walking), improve metabolism through separate ways on the molecular level, also called “molecular pathways.” With ...
Muscle insulin resistance is a hallmark of upper body obesity (UBO) and Type 2 diabetes (T2DM). It is unknown whether muscle free fatty acid (FFA) availability or intramyocellular fatty acid trafficking is responsible for the abnormal response to insulin. Likewise, we do not understand to what extent the incorporation of FFA into ceramides or diacylglycerols (DG) affect insulin signaling and muscle glucose uptake. We will measure muscle FFA storage into intramyocellular triglyceride, intramyocellular fatty acid trafficking, activation of the insulin signaling pathway and glucose disposal rates under both saline control (high overnight FFA) and after an overnight infusion of intravenous ...
The purpose of this study is to improve our understanding of why gastrointestinal symptoms occur in diabetes mellitus patients and identify new treatment(s) in the future.
These symptoms are often distressing and may impair glycemic control. We do not understand how diabetes mellitus affects the GI tracy. In 45 patients undergoing sleeve gastrectomy, we plan to compare the cellular composition of circulating peripheral mononuclear cells, stomach immune cells, and interstitial cells of Cajal in the stomach.
Muscle insulin resistance is a hallmark of upper body obesity (UBO) and Type 2 diabetes (T2DM), whereas lower body obesity (LBO) is characterized by near-normal insulin sensitivity. It is unknown whether muscle free fatty acid (FFA) availability or intramyocellular fatty acid trafficking differs between different obesity phenotypes. Likewise, we do not understand to what extent the incorporation of FFA into ceramides or diacylglycerols (DG) affect insulin signaling and muscle glucose uptake. By measuring muscle FFA storage into intramyocellular triglyceride, intramyocellular fatty acid trafficking, activation of the insulin signaling pathway and glucose disposal rates we will provide the first integrated examination ...
Insufficient sleep may be one of the most common, and most preventable, obesity risk factors. The investigators wish to determine whether 14 nights of modest sleep restriction results in increased energy balance, thus potentially increasing the risk of obesity. The investigators hypothesize that sleep restriction will result in increased energy balance.
To determine if the EndoBarrier safely and effectively improves glycemic control in obese subjects with type 2 diabetes.
The purpose of this study is to evaluate the safety and tolerability of 134 days of daily dosing of HU6, to ealuate the effectiveness of HU6 on weight reduction, and to evaluate the effect of HU6 treatment on exercise capacity.
Using stem cell derived intestinal epithelial cultures (enteroids) derived from obese (BMI> 30) patients and non-obese and metabolically normal patients (either post-bariatric surgery (BS) or BS-naïve with BMI < 25), dietary glucose absorption was measured. We identified that enteroids from obese patients were characterized by glucose hyper-absorption (~ 5 fold) compared to non-obese patients. Significant upregulation of major intestinal sugar transporters, including SGLT1, GLU2 and GLUT5 was responsible for hyper-absorptive phenotype and their pharmacologic inhibition significantly decreased glucose absorption. Importantly, we observed that enteroids from post-BS non-obese patients exhibited low dietary glucose absorption, indicating that altered glucose absorption ...
The purpose of this study is to learn more about how the body stores dietary fat. Medical research has shown that fat stored in different parts of the body can affect the risk for diabetes, heart disease and other major health conditions.
The purpose of this study is to see why the ability of fat cells to respond to insulin is different depending on body shape and how fat tissue inflammation is involved.
The purpose of this study is to determine the mechanism(s) by which common bariatric surgical procedures alter carbohydrate metabolism. Understanding these mechanisms may ultimately lead to the development of new interventions for the prevention and treatment of type 2 diabetes and obesity.
The purpose of this study is to evaluate the usefulness of combining a core liver biopsy guided by endoscopic ultrasound and stomach balloon placement by endoscope for the diagnosis and treatment of fatty liver disease and obesity.
The purpose of this study is to determine the metabolic effects of Colesevelam, particularly for the ability to lower blood sugar after a meal in type 2 diabetics, in order to develop a better understanding of it's potential role in the treatment of obesity.
The purpose of this study is to test whether markers of cellular aging and the SASP are elevated in subjects with obesity and further increased in patients with obesity and Type 2 Diabetes Mellitus (T2DM) and to relate markers of cellular aging (senescence) and the SASP to skeletal parameters (DXA, HRpQCT, bone turnover markers) in each of these groups.
Integration of Diabetes Prevention Program (DPP) and Diabetes Self Management Program (DSMP) into WellConnect.
The purpose of this study is to evaluate if pulsed arterial spin labeling magnetic resonance imaging (PASL MRI) is able to measure a difference in hypothalamic blood flow in patients with anorexia nervosa, opposite than obesity when compared to health.
Endothelial dysfunction, or abnormal functioning of the lining of blood vessels, appears to be a key process in the development of cardiovascular disease. Endothelial dysfunction appears to be caused by both sleep disordered breathing and obesity. As endothelial dysfunction is among the first clinical marker that predicts future cardiovascular events, understanding molecular mechanisms leading to impairment of endothelial function is very important. Endothelial function requires the proper functioning of endothelial nitric oxide synthase (eNOS). eNOS activity is tightly regulated by caveolin-1, a protein important in the formation of cellular structures called caveolae. Low levels of caveolin-1 facilitate optimal nitric oxide ...
The objectives of this study are to identify circulating extracellular vesicle (EV)-derived protein and RNA signatures associated with Type 2 Diabetes (T2D), and to identify changes in circulating EV cargo in patients whose T2D resolves after sleeve gastrectomy (SG) or Roux-en-Y gastric bypass (RYGB).
Muscle insulin resistance is a hallmark of upper body obesity (UBO) and Type 2 diabetes (T2DM). It is unknown whether muscle free fatty acid (FFA) availability or intramyocellular fatty acid trafficking is responsible for muscle insulin resistance, although it has been shown that raising FFA with Intralipid can cause muscle insulin resistance within 4 hours. We do not understand to what extent the incorporation of FFA into ceramides or diacylglycerols (DG) affect insulin signaling and muscle glucose uptake. We propose to alter the profile and concentrations of FFA of healthy, non-obese adults using an overnight, intra-duodenal palm oil infusion vs. ...
The purpose of this study is to learn more about the changes in levels of Spexin, leptin and other biomarkers such as adiponectin and resting energy expenditure before and after hypothalamic surgery.
The purpose of this study is to look at how participants' daily life is affected by their heart failure. The study will also look at the change in participants' body weight. This study will compare the effect of semaglutide (a new medicine) compared to "dummy" medicine on body weight and heart failure symptoms. Participants will either get semaglutide or "dummy" medicine, which treatment participants get is decided by chance. Participants will need to take 1 injection once a week.
This study is being done to better understand the relationship between inflammation in your AT, abnormal deposition of fat around your liver and how this affects its appearance and function and ultimately insulin resistance.
This study aims to evaluate the mechanisms leading to hyperoxaluria and increased risk of kidney stone formation after bariatric surgery.
This randomized phase III trial studies whether weight loss in overweight and obese women may prevent breast cancer from coming back (recurrence). Previous studies have found that women who are overweight or obese when their breast cancer is found (diagnosed) have a greater risk of their breast cancer recurring, as compared to women who were thinner when their cancer was diagnosed. This study aims to test whether overweight or obese women who take part in a weight loss program after being diagnosed with breast cancer have a lower rate of cancer recurrence as compared to women who do not take ...
The purpose of this study is to see if there is a connection between bad experiences in the patient's childhood, either by the patient or the parent, and poor blood sugar control, obesity, poor blood lipid levels, and depression in patients with type 1 diabetes.
The purpose of this study is to evaluate the effect of Aramchol as compared to placebo on NASH resolution, fibrosis improvement and clinical outcomes related to progression of liver disease (fibrosis stages 2-3 who are overweight or obese and have prediabetes or type 2 diabetes).
A variety of liver insults lead to pathological changes in liver architecture that culminate in cirrhosis. While invasive liver biopsy was required to detect cirrhosis, the development of magnetic resonance elastography (MRE) has revolutionized our ability to detect liver fibrosis through non-invasive means that involve measurement of liver stiffness. However, a number of pathological findings occur in liver in response to various insults that precede cirrhosis and are clinically important to identify such as steatosis associated with NASH, inflammation associated with viral hepatitis, and congestion associated with cardiac hepatopathy. Detection of such entities provides essential diagnostic, prognostic, and treatment information ...
The purpose of this study is to determine whether short-term treatment with Fisetin reduces the rate of death and long term complications related to COVID-19.
The purpose of this study is to evaluate the effietiveness of remdesivir (RDV) in reducing the rate of of all-cause medically attended visits (MAVs; medical visits attended in person by the participant and a health care professional) or death in non-hospitalized participants with early stage coronavirus disease 2019 (COVID-19) and to evaluate the safety of RDV administered in an outpatient setting.
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- Volume 5, Issue 7
- A comparison study on the prevalence of obesity and its associated factors among city, township and rural area adults in China
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- Yan Zou 1 ,
- Ronghua Zhang 1 ,
- Biao Zhou 1 ,
- Lichun Huang 1 ,
- Jiang Chen 1 ,
- Fang Gu 1 ,
- Hexiang Zhang 1 ,
- Yueqiang Fang 1 ,
- Gangqiang Ding 2
- 1 Nutrition and Food safety Department , Zhejiang Provincial Center for Disease Control and Prevention , Hangzhou , China
- 2 National Institute for Nutrition and Health , Beijing , China
- Correspondence to Ronghua Zhang; zouyan910{at}yeah.net
Objectives To explore the association of dietary behaviour factors on obesity among city, township and rural area adults.
Setting A stratified cluster sampling technique was employed in the present cross-sectional study. On the basis of socioeconomic characteristics, two cities, two townships and two residential villages were randomly selected where the investigation was conducted.
Participants A total of 1770 city residents, 2071 town residents and 1736 rural area residents participated in this survey.
Primary and secondary outcome measures Dietary data were collected through interviews with each household member. Anthropometric values were measured. Participants with a body mass index (BMI) of ≥28.0 kg/m 2 were defined as obesity.
Results The prevalence of obesity was 10.1%, 7.3% and 6.5% among city, township and rural area adults, respectively. Correlation analysis showed that for adults living in cities, the daily intake of rice and its products, wheat flour and its products, light coloured vegetables, pickled vegetables, nut, pork and sauce was positively correlated with BMI (r=0.112, 0.084, 0.109, 0.129, 0.077, 0.078, 0.125, p<0.05), while the daily intake of tubers, dried beans, milk and dairy products was negatively correlated with BMI (r=−0.086, −0.078, −0.116, p<0.05). For township residents, the daily intake of vegetable oil, salt, chicken essence, monosodium glutamate and sauce was positively correlated with BMI (r=0.088, 0.091, 0.078, 0.087, 0.189, p<0.05). For rural area residents, the daily intake of pork, fish and shrimp, vegetable oil and salt was positively correlated with BMI (r=0.087, 0.122, 0.093, 0.112, p<0.05), while the daily intake of dark coloured vegetables was negatively correlated with BMI (r=−0.105, p<0.05).
Conclusions The prevalence of obesity was higher among city residents than among township and rural area residents. The findings of this study indicate that demographic and dietary factors could be associated with obesity among adults. Healthy dietary behaviour should be promoted and the ongoing monitoring of population nutrition and health status remains crucially important.
- NUTRITION & DIETETICS
- PREVENTIVE MEDICINE
- PUBLIC HEALTH
This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
http://dx.doi.org/10.1136/bmjopen-2015-008417
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Strengths and limitations of this study
The present study is one of the few studies to examine the prevalence of obesity and its associated factors among city, township and rural area adults. Its strengths also include the large sample size and stratification of the analyses by region to observe the difference between a city, township and rural area. We were able to examine the association between a variety of demographic and dietary factors and body mass index. We had data on sociodemographic and dietary behaviour variables with which we were able to comprehensively analyse the difference among city, township and rural area adults.
One limitation of the study is the cross-sectional design that disallows a sequence of temporality to be established for obesity and dietary behaviour. Residents with obesity may have changed their diet based on their clinician's suggestions. If they then ate a healthy diet, the dietary influence detected may be the result, but not the cause, of obesity. If it is true, then this healthy diet may in some cases drive the association to be null and make our findings under-reported. Future prospective cohort studies are warranted to verify our findings.
Introduction
Obesity represents a rapidly growing threat to the health of populations in an increasing number of countries. Indeed, they are now so common that they are replacing more traditional problems such as under nutrition and infectious diseases as the most significant causes of ill health. Between 1980 and 2008, the mean global body mass index (BMI) increased by 0.4–0.5 kg/m2 per decade in men and women. 1 Obesity is associated with the incidence of multiple comorbidities including type II diabetes, cancer and cardiovascular diseases. 2 The worldwide prevalence has more than doubled since 1980. A number of studies have reported that with each surge in weight, there is an increase in the risks for coronary heart disease, type 2 diabetes, cancers (endometrial, breast and colon), hypertension, dyslipidaemia, stroke, sleep apnoea, respiratory problems, osteoarthritis and gynaecological problems. 3 The trend in the rising prevalence of obesity and related morbidity and mortality in developing countries has been attributed to rapid urbanisation, nutrition transition and reduced physical activity. 4
China has had a history of under-nutrition followed by the most rapid increase in obesity and related diseases worldwide, with differential rates across rural and urban areas. 5 Owing to various factors such as geographical environment, living habits and dietary behaviour, people in different regions have different epidemic characteristics and dietary behaviour, which may be associated with the risk of obesity. The aim of this study was to explore the association between a variety of demographic and dietary behaviour factors and obesity among city, township and rural area adults.
Subjects and methods
A stratified cluster sampling technique was employed in this cross-sectional study. On the basis of socioeconomic characteristics, two cities, two townships and two residential villages were randomly selected where the investigation was conducted. The city is defined as the centre area of the big city, and the township is defined as all the district and county cities. The residential village is defined as a county. In every sampling unit, 450 households were selected by the random sampling method according to the household registration information. Then every member of the sampled household was interviewed.
During home visits spanning 3 d, dietary data were collected through interviews with each household member, including rice and its products, wheat flour and its products, tuber, bean products, dark coloured vegetables, light coloured vegetables, pickled vegetables, pork, poultry, milk and dairy products, eggs, fish and shrimp, vegetable oil, sugar and starch, salt, chicken essence, monosodium glutamate and sauce. The questionnaire was administrated face to face by trained staff through door to door interview. Information about other covariables was also collected including educational level, physical activity level, smoking, drinking and lifestyle. All subjects provided written informed consent after the research protocols were carefully explained to them.
Anthropometric measurements
Height was measured without shoes to the nearest 0.2 cm using a portable SECA stadiometer, and weight was measured without shoes and in light clothing to the nearest 0.1 kg on a calibrated beam scale. Waist circumference was measured at a point immediately above the iliac crest on the midaxillary line at minimal respiration to the nearest 0.1 cm. 6 BMI was calculated by weight (kg)/height(m) 2 . Participants with a BMI of ≥28.0 kg/m 2 were defined as obese. 7
Statistical analysis
As continuous variables were not normally distributed, they were described as the median, 25th and 75th centiles. The differences between rural residents and urban residents were evaluated by nonparametric test (Mann-Whitney test). The distributions of potential influencing factor proportions were compared by the χ 2 test. Spearman correlations were used to explore the correlations between dietary factors and BMI. Spearman's r was used to describe the strength of the relationship between two variables. Data processing and statistical analyses were performed using the SAS 9.2 software. All tests were two sided and the level of significance was set at p<0.05.
Demographic and dietary intake characteristics
A total of 1770 city residents, 2071 town residents and 1736 rural area residents participated in this survey. The prevalence of obesity was 10.1%, 7.3% and 6.5% in city, township and rural area adults, respectively (χ 2 =15.656, p=0.000). The median value (25th, 75th centile) of BMI was 23.0 (20.2, 25.3), 22.2 (19.6, 24.7), 21.6 (19.1, 24.1) among adults in the three types of region, respectively (H=97.749, p=0.000).
The demographic and dietary intake characteristics are presented in table 1 . When the demographic and dietary intake variables were stratified by region, there were significant difference on BMI, weight, waist circumstance among city, township and rural area adults with the same direction (p<0.05). Among city residents, the intake of rice and its products and pickled vegetables was higher in obese adults than in non-obese adults (p<0.05). Among township residents, wheat flour and its products, salt and monosodium glutamate were higher in obese adults than in non-obese adults (p<0.05). There were no significant differences in dietary intake among rural area adults.
- View inline
Demographic characteristics and dietary intake from a reported 24 h dietary recall in adults, Zhejiang province, China
Demographic characteristics and dietary behaviour distribution are presented in table 2 . Among city residents, the distributions of education level, number of family members living together, drinking high alcohol liquor and drinking Yellow Wine were significant between obese adults and non-obese adults (p<0.05). Among township and rural area residents, there were no significant differences in the distribution of these covariables (p>0.05).
Demographic characteristics and dietary behaviour in adults, Zhejiang province, China
Correlations between dietary factors
Correlation analysis showed that for adults living in cities, the daily intake of rice and its products, wheat flour and its products, light coloured vegetables, pickled vegetables, nut, pork and sauce was positively correlated with BMI (r=0.112, 0.084, 0.109, 0.129, 0.077, 0.078, 0.125, p<0.05), while the daily intake of tubers, dried beans, milk and dairy products was negatively correlated with BMI (r=−0.086, −0.078, −0.116, p<0.05). For township residents, the daily intake of vegetable oil, salt, chicken essence, monosodium glutamate and sauce was positively correlated with BMI (r=0.088, 0.091, 0.078, 0.087, 0.189, p<0.05). For rural area residents, the daily intake of pork, fish and shrimp, vegetable oil and salt was positively correlated with BMI (r=0.087, 0.122, 0.093, 0.112, p<0.05), while the daily intake of dark coloured vegetables was negatively correlated with BMI (r=−0.105, p<0.05) ( table 3 ).
Correlations between BMI and daily dietary intake among adults living in cities, townships and rural area, Zhejiang province, China
This study employed an analytical approach that provides insight into two types of commonly recognised risk factors for adult obesity—demographic and dietary factors.
In recent decades, the double burden of malnutrition—the coexistence of under-nutrition and over-nutrition in the same population—has become a prominent public health concern in transitional countries. Traditional diet has been replaced by the ‘Western diet’ and major declines in all phases of activity and increased sedentary activity as the main reasons explaining the rapid increase in overweight and obesity, bring major economic and health costs. 8–10
According to a study carried out among Chinese urban children and adolescents (aged 7–18 years) in 2000, the prevalence of obesity in boys was 6.5% in Beijing, 4.9% in Shanghai, 4.5% in coastal big cities, and 2.0% in coastal medium/small-sized cities, respectively, while the prevalence of obesity and overweight in girls of the same age group was 3.7% in Beijing, 2.6% in Shanghai, 2.8% in coastal big cities, and 1.7% in coastal medium/small-sized cities, respectively. 11 The China Health and Nutrition Surveys reported that the prevalence of obesity in children aged 7–17 increased from 5.2% in 1991 to 13.2% in 2006, and the most noticeable increase was in children from urban areas and those from higher income backgrounds. 12 In our study, the prevalence of obesity reached 10.1%, 7.3% and 6.5% among city, township and rural area adults in Zhejiang province. The prevalence of obesity in the coastal big cities, followed by that in the township cities, had reached the average level of the developed countries, and the result was consistent with Ji CY's study. 13 Ji CY also reported that the prevalence of obesity was low in most of the inland cities at an early stage of epidemic overweight. The epidemic manifested a gradient distribution in groups, which was closely related to the socioeconomic status of the populations. 13 This was also consistent with the previous report that a higher prevalence of obesity was observed in the more educated, urban, high income and high social status segments of society. 14–17 Recently, in Drewnowski A's study, census tract level home values and college education were more strongly associated with obesity than household incomes. For each additional $100 000 in median home values, the census tract obesity prevalence was 2.3% lower. The three socioeconomic status factors together explained 70% of the variance in census tract obesity prevalence. 18
There was a pattern that the risk of obesity was greater among city residents with higher education. It seems possible that the education level may be complicating the relationship between dietary behaviour and obesity. On the one hand, residents with a higher education level are more likely to endorse health ideals such as a more healthy diet or physical activities to preserve a good body image, 19 and linked to a lower prevalence of obesity among city residents, and the result was consistent with previous studies. 20–21 On the other hand, a higher education level may be associated with clerical work or increased sitting time among township residents and rural residents, which one might expect would increase the risk of obesity; thus, we could not find the effect of education level on the risk of obesity in a township and rural area. In addition, this inconsistency between city and township residents and rural area residents was similar to the opinion that an initial increase from low social economic status to mid-level social economic status was associated with worse health outcomes and behaviours; however, the continued increase from mid-social economic status to high social economic status saw returns to healthy outcomes and behaviours. 22
The major finding of dietary factors among city residents was that residents with obesity have a higher daily intake of rice and its products and pickled vegetables. BMI increased with the daily intake of rice and its products, wheat flour and its products, light coloured vegetables, pickled vegetables, nut, pork and sauce and decreased with the daily intake of tubers, dried beans, milk and dairy products. In a township, residents with obesity have a higher daily intake of vegetable oil, salt, chicken essence, monosodium glutamate and sauce. The major finding among rural area residents was that BMI increased with the daily intake of pork, fish and shrimp, vegetable oil and salt, but decreased with the daily intake of dark coloured vegetables. The differences in relationship between dietary factors and BMI among city, township and rural area residents may be due to the different dietary patterns, as reported in the literature, 23 but a daily intake of salt and foods high in salt and sugar such as sauce, chicken essence and pickled vegetables was associated with high BMI. This was consistent with the ecological study of the UK and other previous studies. 24–26 Also, a Swiss study found a positive association between obesity and salt intake. 27 This was also consistent with the policy and action on nutrition and health promotion in many countries. In the UK, a wide range of policies are in place, including support for breastfeeding and healthy weaning practices, nutritional standards in schools, restrictions on marketing foods high in fat, sugar and salt to children, schemes to boost participation in sport, active travel plans, and weight management services. 28–29 In recent years, there has been increased interest in the public health benefit of small changes to behaviours. The developing world needs to give far greater emphasis to addressing the prevention of the adverse health consequences of this shift to the nutrition transition stage.
Among city residents, the daily intake of milk and dairy products was associated with low BMI; this result was similar to the results of a random-sample population-based study in Córdoba, Argentina. 30 Among rural residents, the daily intake of dark coloured vegetables was associated with low BMI, while the daily intake of vegetable oil was associated with high BMI. The obesity problem needs to be tackled differently in the city, township and rural area as their correlated dietary factors are not the same.
In conclusion, this study extends our understanding of demographic and dietary influencing factors on obesity among city, township and rural area residents. Obesity is still highly prevalent among Chinese adults. The prevalence of obesity was higher in city residents than in township and rural area residents. Our results call for urgent action to educate people in diet style modifications and the need for effective preventive and educational strategies on obesity.
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- ↵ Centers for Disease Control and Prevention, “Overweight and obesity 2012,” 2013 . http://www.cdc.gov/obesity/adult/causes/index.html
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- ↵ Centers for Disease Control and Prevention (updated 2012) Defining Overweight and Obesity. http://www.cdc.gov/obesity/defining.html (accessed Sep 2012 ).
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- De La Quintana AG , et al
Contributors RZ, YZ and GD were responsible for the study design. YZ was responsible for the analysis, paper writing and revision. RZ, BZ, FG, JC, LH, HZ and YF took part in the field investigation and data collection. BZ, LH, HZ and YF were in charge of laboratory detection. All authors contributed to the discussion and interpretation of the data and to the writing of the manuscript.
Funding This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Patient consent Obtained.
Ethics approval The study protocol was approved by the ethics committee of Zhejiang provincial center for disease control and prevention.
Provenance and peer review Not commissioned; externally peer reviewed.
Data sharing statement No additional data are available.
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Epidemiology and Population Health
Non-traditional data sources in obesity research: a systematic review of their use in the study of obesogenic environments
- Julia Mariel Wirtz Baker ORCID: orcid.org/0000-0002-6348-7739 1 , 2 ,
- Sonia Alejandra Pou ORCID: orcid.org/0000-0002-8571-9318 1 , 2 na1 ,
- Camila Niclis ORCID: orcid.org/0000-0002-0117-4315 1 , 2 ,
- Eugenia Haluszka ORCID: orcid.org/0000-0002-9511-8882 1 , 2 &
- Laura Rosana Aballay ORCID: orcid.org/0000-0002-3430-3566 2 na1
International Journal of Obesity volume 47 , pages 686–696 ( 2023 ) Cite this article
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- Epidemiology
The complex nature of obesity increasingly requires a comprehensive approach that includes the role of environmental factors. For understanding contextual determinants, the resources provided by technological advances could become a key factor in obesogenic environment research. This study aims to identify different sources of non-traditional data and their applications, considering the domains of obesogenic environments: physical, sociocultural, political and economic.
We conducted a systematic search in PubMed, Scopus and LILACS databases by two independent groups of reviewers, from September to December 2021. We included those studies oriented to adult obesity research using non-traditional data sources, published in the last 5 years in English, Spanish or Portuguese. The overall reporting followed the PRISMA guidelines.
The initial search yielded 1583 articles, 94 articles were kept for full-text screening, and 53 studies met the eligibility criteria and were included. We extracted information about countries of origin, study design, observation units, obesity-related outcomes, environment variables, and non-traditional data sources used. Our results revealed that most of the studies originated from high-income countries (86.54%) and used geospatial data within a GIS (76.67%), social networks (16.67%), and digital devices (11.66%) as data sources. Geospatial data were the most utilised data source and mainly contributed to the study of the physical domains of obesogenic environments, followed by social networks providing data to the analysis of the sociocultural domain. A gap in the literature exploring the political domain of environments was also evident.
The disparities between countries are noticeable. Geospatial and social network data sources contributed to studying the physical and sociocultural environments, which could be a valuable complement to those traditionally used in obesity research. We propose the use of information available on the Internet, addressed by artificial intelligence-based tools, to increase the knowledge on political and economic dimensions of the obesogenic environment.
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Data availability
The datasets generated during the current study are available from the corresponding author upon reasonable request.
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Acknowledgements
This research was partially supported by the National Science and Technology Agency (FONCyT) grants PICT-2020-A-03283 and PICT-2019-2019-04594.
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These authors contributed equally: Sonia Alejandra Pou, Laura Rosana Aballay.
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Health Sciences Research Institute (INICSA), National Council of Scientific and Technical Research (CONICET), Faculty of Medical Sciences, National University of Córdoba, Bv. De La Reforma, Ciudad Universitaria, Zip Code 5000, Córdoba, Argentina
Julia Mariel Wirtz Baker, Sonia Alejandra Pou, Camila Niclis & Eugenia Haluszka
Human Nutrition Research Centre (CenINH), School of Nutrition, Faculty of Medical Sciences, National University of Córdoba, Bv. De La Reforma, Ciudad Universitaria, Zip Code 5000, Córdoba, Argentina
Julia Mariel Wirtz Baker, Sonia Alejandra Pou, Camila Niclis, Eugenia Haluszka & Laura Rosana Aballay
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JMWB was responsible for writing the main draft of the report, conducting the search, screening potentially eligible studies, extracting and analysing the data, interpreting the results, creating the results tables, and discussing studies. CN and EH were responsible for extracting articles, screening potentially eligible studies, and providing feedback on the report. SAP and LRA were responsible for the design of the review protocol and the arbitrating studies selected by the authors, contributing to the writing of the report and the table of results, analysing and interpreting the results, and discussing with other studies. All the authors critically read and approved the final manuscript.
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Correspondence to Laura Rosana Aballay .
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Wirtz Baker, J.M., Pou, S.A., Niclis, C. et al. Non-traditional data sources in obesity research: a systematic review of their use in the study of obesogenic environments. Int J Obes 47 , 686–696 (2023). https://doi.org/10.1038/s41366-023-01331-3
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Health Vol.5 No.8C(2013), Article ID:36211,12 pages DOI:10.4236/health.2013.58A3010
Qualitative studies of obesity: A review of methodology
Ian Brown * , Jill Gould
Centre for Health & Social Care Research, Sheffield Hallam University, Sheffield, UK; * Corresponding Author: [email protected]
Copyright © 2013 Ian Brown, Jill Gould. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Received 25 June 2013; revised 25 July 2013; accepted 10 August 2013
Keywords: Obesity; Stigma; Qualitative Methods; Researcher Reflexivity
BACKGROUND: There is a developing interest in qualitative research to understand the perspectives and experiences of people living with obesity. However, obesity is a stigmatised condition associated with negative stereotypes. Social contexts emphasizing large body size as a problem, including research interviews, may amplify obesity stigma. This study reviews the methodology employed by qualitative studies in which study participants were obese and data collection involved face-to-face interviews. METHODS: Database searches identified qualitative studies meeting inclusion criteria from 1995 to 2012. Following screening and appraisal data were systematically extracted and analyzed from 31 studies. RESULTS: The studies included 1206 participants with a mean age of 44 years and mean BMI of 37 kg/m 2 . Women (78.8%) outnumbered men (21.2%) by four to one. Socio-economic background was not consistently reported. The studies employed similar, typically pragmatic, qualitative methodologies, providing rich textual data on the experience of obesity derived from face-to-face interviews. The majority considered quality issues in data collection, analyses and generalizability of findings. However, the studies were weak as regards researcher reflexivity in relation to interviewer characteristics and obesity stigma. CONCLUSIONS: The impact of obesity stigma has not been attended to in the qualitative research. Clear information about study participants is essential, but studies involving face-to-face interviews should also report on interviewer characteristics including body size.
1. INTRODUCTION
Qualitative studies have become an accepted methodology within health research [1-2]. Advocates note the strength of qualitative methods in delivering a greater depth of understanding of, for example, the complex phenomena faced by patients living with long term conditions [3-4]. Appreciation of the methods, quality criteria and reporting standards needed for rigorous qualitative research has also become established; and a number of excellent checklists and guides are available [5-7]. Systematic reviews and syntheses of qualitative studies are recognized as a useful contribution to evidence and policy development [8-9].
Core definitions of qualitative research point up the value of flexibility within an emergent design in which textual data are acquired to explore social phenomena in context [10]. In practice, in health and medical research, the data are typically gathered from individual or group interviews or, less frequently, from observation of interactions such as between patient and clinician within a consultation. Analyses typically proceed through iterative stages of coding data to inductively develop, for example, themes, frameworks and theories [11].
Building on previous guidelines and an extensive literature review, the COREQ checklist is useful for studies employing interviews and focus groups [7]. Criteria are grouped within three domains. In the first, labeled “research team and reflexivity”, attention is drawn to how characteristics of the research team and relationships with participants affect responses, interpretation of data and hence credibility of findings. The second domain highlights how the study’s theoretical framework (methodology), sampling, setting, data collection methods affect study quality and findings. The third domain focuses on data analysis, interpretation and reporting.
Obesity is viewed as a long term medical condition and is currently one of great concern for public health because of obesity’s increasing prevalence and the associated risks for diabetes and other chronic diseases [12- 14]. There has been growing interest in the perspectives and experiences of patients living with obesity and a developing appreciation of the degree to which obesity is a stigmatized condition, associated with negative attitudes and discrimination in many countries [15,16]. People who are obese face difficulties in various spheres of life, such as in education and employment. Derogatory portrayals of obesity are common within the culture and media of these societies.
Stigma is the phenomenon in which societal evaluations negatively impact on individuals’ sense of identity and self-presentation [15]. In some societies, obesity brings a strongly devalued physical and moral identity, creating challenges for those affected by obesity in managing their identity and in presenting themselves in social interaction. Obesity stigma has general consequences in many spheres of life for affected individuals. However, interactions oriented to obesity and therefore emphasizing large body size as a problem, are a context in which stigma will be amplified [16]. This has important, but uncharted, consequences for research about obesity, particularly, research involving face-to-face interaction in data collection.
In this paper, we report on a literature review of qualitative studies in which the study participants were adults categorized as obese and the data collection involved face-to-face methods.
2.1. Design and Searches
We employed established methods in searches, appraisal, data extraction and analysis of relevant literature [17-19]. We eventually included 31 qualitative studies of obesity in which all, or the great majority, of participants were obese and data collection employed face-to-face methods. The studies were drawn from a range of disciplines after electronic, lateral and key journal searches covering the period January 1995 to July 2012. The databases included: AMED (Ovid); CENTRAL (Cochrane Library); CINAHL (Ebsco); Medline (Ebsco); PsychINFO (CSA); SCOPUS; Web of Science (ISI Web of Knowledge).
Search terms were employed to identify all studies reporting findings on experiences of obesity derived from inductive analysis of qualitative data. An illustrative search in CINAHL with search terms is shown in Table 1 . We used search and screening tools within each database
Table 1 . Illustrative search (CINAHL).
to include synonyms, word variants, database labels and to remove duplicates and exclude studies not meeting our criteria. Only English language studies were included.
2.2. Exclusions and Analyses
After independently screening of 417 study abstracts, we were able to exclude the majority (356) because they were not a qualitative study involving adult participants.
We appraised the full report of 61 studies and excluded 30 studies for the following main reasons: nine did not provide sufficient information about how data were collected and analyzed or about participant characteristics to be sure participants were mainly obese; seven the sample majority were normal weight or underweight; five the focus was not obesity with inductive analysis of qualitative data; five did not use face-to-face data collection methods; three the sample were not adults; and in one duplicate findings were reported in more detail in an included study.
Methodology information was systematically extracted from the 31 included study reports and summarized in matrices for analysis. Both authors checked extracted data against the original study report. Both authors worked initially independently to identify and then agree on key themes and issues from the extracted data.
Included studies are summarized within Table 2 [20- 52]. Typically these studies aimed to explore and describe adults’ perceptions and experiences of obesity and of weight management interventions. Our present focus is on the methodology of the reviewed studies not their
Table 2 . Summary of reviewed studies.
findings. However, in passing, it should be noted that the majority (22 of 31 studies) highlight in their findings, at least to some degree, the influence of obesity stigma on participants’ perceptions and experiences.
3.1. Contexts and Recruitment
The majority of reports are from authors working in academic institutions in developed countries. Most of the studies are focused on urban populations in these countries. Recruitment settings are divided between community samples (16 studies) and primary health care, outpatient samples and hospital (15 studies). A mix of settings and recruitment strategies is used in the larger studies; some of the community based studies recruited participants active in commercial slimming programs. The sampling setting appears to have been convenience but several studies make a virtue of recruiting either patients or a non-patient community sample in considering the application of findings. Just over half (17) of the studies recruitment contexts are closely linked with interventions to lose weight—study interviews were within a weight management intervention.
3.2. Participant Characteristics
Overall 958 different individuals were involved in the studies (1206 participants if including repeat samples of same individuals within different studies). Women (78.8%) outnumbered men (21.2%) by a ratio of four to one. The best estimate of the mean age of participants is 44 years (mean age was not reported in all studies). Participants mean BMI could be estimated at 37 kg/m 2 overall; again the mean is not consistently reported. Thirteen studies reported only a BMI range indicating obese participants. The socio-economic background of participants was not reported consistently.
3.3. Methodological Approach
Understandably, given space constraints, very few of the reviewed studies reported their methodological approach in any detail but most summarize the approach with reference to established sources. However, in some studies it was difficult to discern any distinct methodological underpinning. Nine studies refer sufficiently to Grounded Theory to be clear that this was the main theoretical underpinning. Six other studies also refer to Framework Analysis and others to variants of Thematic and Content analysis. Notwithstanding the scantiness and apparent diversity in methodological underpinnings the actual practice of research was similar across studies. Purposive sampling of convenience populations with face-to-face group or individual interviews employed. Twenty one studies (67.7%) involved individual in depth interviews; the remaining ten studies (32.3%) employed focus group methods. Analyses proceeded through multiple stages refining data coding to support inductive analyses.
3.4. Interviewers and Reflexivity
All the studies involved participants who would be categorized as medically obese (BMI 30+ kg/m 2 ). Information on interviewer characteristics was very limited as was discussion of reflexivity. Indeed 22 studies (70.9%) report nothing about the interviewer characteristics. Nine studies do provide some description, mainly of interviewer occupation, gender and ethnicity where this appears relevant to the groups being interviewed. Only three studies give attention to the body size characteristics of the interviewer. The reports from Chan and Gillick [26] and from Granberg [30] are both vague but indicate the interviewers experienced body weight problems themselves. The report from Diaz, et al. [29] is the only one that is explicit in stating that the focus groups were conducted by one normal weight investigator and one overweight aide.
The limitations discussed within the study reports are very weak as regards researcher reflexivity. Eight studies (25.8%) did not include any substantive discussion of limitations. The majority (20 studies, 64.5%) discuss limitations but only in conventional terms for qualitative methods: for example, of potential biases arising from self-selection and convenience sampling, of limits to the generalizability or transferability of findings from a small sample, of potential limitations of group as against individual interviews for acquiring personal views. Only three study reports reflected on how interviewer characteristics could have affected data collection processes and findings. Chan and Gillick [26] and Granberg [30] consider how their own characteristics may have affected recruitment and comfort of participants. Jones and colleagues [35] note that participants may have felt uncomfortable if the interviewer was also a dietician.
4. DISCUSSION
4.1. Review Summary
As far as possible a comprehensive and systematic approach has been taken in this review of the methodology employed in qualitative studies of adults’ experiences of obesity. However, the diverse range and variable quality of studies has necessitated a more exploratory and open review method. A judgment was reached to include studies on the basis that it was clear that most participants were obese and the data were collected by face to face interview. We did not attempt to otherwise weed out weaker studies because we were not concerned with the findings of the studies but with their reported methods. Nevertheless, our review has brought out important issues for qualitative research methods with respect to obesity and allows useful but provisional recommendations to be made about the design and reporting of such studies.
4.2. Strengths in Reviewed Studies
The COREQ guidance for assessing quality in research highlights the value of explicit details of the theoretical position and methods [7]. The theoretical framework has consequences for the approach to establishing the quality and rigor of the study. Our review shows that were this to be strictly enforced then nearly a third of studies of obesity would fall short. However, researchers face a challenge within a short article to provide detailed methodological background. There is also the danger of articles reproducing long justifications that belong in epistemology journals rather than health and social research journals. The majority of studies of obesity provide sufficient pragmatic information appropriate to the publication context and most report clearly the study setting, sampling and methods of data collection with attention to quality issues within these methods.
Likewise, on the whole, the reporting of data analysis and interpretation methods is to a good standard. A better consistency in reporting participant characteristics such as socio-economic background, mean ages and BMI is needed and this is further discussed below. Finally, among strengths, the studies present rich data delivering a depth of understanding of the experiences, in their own words, of people living with obesity. Nevertheless, these strengths must be set against limitations in sampling and a stark lack of researcher reflexivity given the focus of the studies.
4.3. Limitations in Reviewed Methodologies
Whilst obesity affects all social groups it is important in the context of medical research to consider health inequalities more carefully. Inequalities linked to obesity are complex and shifting [14,51]. There is evidence for social class and ethnicity divisions in the prevalence of obesity and, very clearly, in the health consequences of obesity such as diabetes [51-53]. In common with most clinical studies, the qualitative research about obesity is likely to be biased to those who are better off, middle aged, better educated and without the more disabling comorbidities that make participation in research difficult. However, the socio-economic biases in particular are difficult to judge from the reviewed papers and this is an important limitation.
Age and gender are more consistently reported. In most societies, obesity prevalence peaks for both men and women in late middle age; so it is perhaps reasonable that the qualitative research reflects a middle aged perspective. Less justifiable is the bias towards women in a ratio of four to one. Obesity is projected to affect a greater proportion of men than women [12-14,52] and it will be critical to understand the distinct perspective and experiences of men rather than generalize from studies of women.
A further important limitation is the lack of attention to how interviewer characteristics influence data collection. Ironically, even the studies concluding that obesity stigma was a key finding did not attend to its potential impact on their own data collection. The evidence more broadly about stigma and obesity stigma in particular indicates that it is a deep rooted psycho-social phenomenon, not readily under conscious control [15]. Communication skills to establish a good rapport with a participant and to maintain a comfortable and non-judgmental setting are critical in interview methods [54]. Even so, researchers employing face-to-face methods must recognize that people are conscious of obesity stigma and, therefore, the interview interaction presents a heightened challenge as regards management of self and identity. Participants will almost certainly alter their responses to questions as against their perceptions of the size of the interviewer and other influences in the context of the interview. Of course, within a qualitative methodology there is no true or false simple reality—just a greater demand, as in the COREQ criteria, for reflexivity as to the contexts and influences on the data generated.
Within qualitative research telephone interviews have generally been regarded as a weaker method, less able to provide rich data than face-to-face interviews [55]. However, this general tenet appears to be based on assumptions about how people traditionally behaved using telephones rather than empirical evidence. Where telephone interviews have been employed (particularly with harder to reach groups and where a degree of social stigma may be present within face-to-face work) the reports of data quality are positive, and this includes studies of obesity [56-59]. The advantages of telephone interviews are worth reiterating. First, it potentially makes the study more accessible to participants reluctant to arrange a face-to-face interview; this may include men. Second, it removes the effects of the body size of the interviewer from influencing the data. Telephone interviews have potential, therefore, and might be considered in study design as an alternative to face-to-face methods. However, the evidence of advantages and disadvantages is still limited with respect to obesity.
4.4. Conclusion
Methodologically pragmatic studies are improving understanding of the experience of obesity. The studies are of variable quality and the impact of obesity stigma, a deep rooted psycho-social phenomenon in most societies, has not been attended to in the methodology of these studies. The implications for qualitative research of obesity stigma are therefore unclear. Researchers should consider the sampling biases in previous studies, particularly with a view to involving more men. Clearer information about study participants, including socio-economic background, would be helpful. Studies involving face-to-face interviews should report on salient interviewer characteristics including body size. In time, this will provide a clearer picture of how these characteristics might affect data collection and study findings.
5. ACKNOWLEDGEMENTS
This study was in receipt of funding from the Collaborations for Leadership in Applied Health Research and Care for South Yorkshire (CLAHRC SY). CLAHRC SY acknowledges funding from the National Institute for Health Research (NIHR). The views and opinions expressed are those of the authors, and not necessarily those of the NHS, the NIHR or the Department of Health.
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