AuthorLiliana Andrei, Catalina
  1. Introduction

    Since its creation by the Belgian scientist, Quetelet, more than a century and a half ago (Garrow and Webster, 1985), the body mass index (BMI), because of its ease of calculation and interpretation, has emerged as a good predictor of positioning a particular person regarding what accepted standards (e.g., WHO, 2006) consider as normal.

    Certainly there are many works (Sturm, 2007 or Farrant et al., 2013 just to name a few) who consider that BMI should be contextualized by region (country, continent), age or gender. However, BMI continues to be successfully used in measuring the desirable weight that a person ought to have according to height. As it is known, the formula for calculating this indicator is:

    BMI = Mass(kg)/[(Height(m)).sup.2]

    According to WHO (2006) obesity (OB) occurs when BMI>30, severe obesity (SO) occurs when BMI> 35 and severe extreme obesity (SEO) occurs when BMI> 40. Just as in other Western countries the prevalence of obesity in recent years in Romania is in a continuous growth (Afshin et al., 2017; Barbu et al., 2015). The negative effects of SO and SEO become, nowadays, common knowledge (Haslam and James, 2005; Afshin et al., 2017). Firstly, a major impact was observed on life expectancy where persons with SO may register 6-7 lost years while SEO may induce a loss of 10 years. The second negative effect is related to the morbidity. There are major demonstrated connections between SO and SEO and illnesses like: diabetes, hypertension, coronary artery disease, stroke and arthritis (Wang et al., 2017). Thirdly, it is about higher costs regarding health care for persons being affected by SO and/or SEO (Andreyeva, Sturm and Ringel, 2004). One of the aims of our paper is to provide an estimation for this third negative effect in Romania.

    The paper is structured in a classical manner. The second section highlights the data and the methods, the third one provides mainly data analysis, and the fourth section estimates the financial burden of the obesity in Romania while the last section concludes.

  2. Source of data and methodology

    This article analyzes statistical information published by the National Statistics Institute in 2008 (like Ausloos, Herteliu and Ileanu, 2014) following the implementation of an EU-funded project by a consortium of Statistics Sweden, ICON Institute, Digital Data Services and Irecson Institute. The project was entitled 'The health of the population of Romania'. This project was part of a wider European one: European Health Interview Survey (EHIS) which occurred in all EU countries in 2008 (Eurostat, 2015). In the 2008 project, a questionnaire was applied to a representative sample consisting of 10,140 regional households all over the country. Within these households, 21,428 interviews were conducted (about 88% of them comprised adult persons, while 12% children). In the analysis of BMI only those persons with at least 18 years were taken into account.

    In terms of territorial analysis, it is worth mentioning that according to the European body for statistics (Eurostat) the national territory is divided into hierarchical levels according to the NUTS classification (Nomenclature of territorial units for statistics) [1].

    In our approach we will use specific methods (descriptive statistics) and, where appropriate, some statistical tests (Chi Square and other similar) to validate or not the consistency/ associations between variables. Statistical analyzes were performed using Excel. Graphs were designed with PowerPoint, and maps using ArcGIS software. Following this approach, our paper aims to provide an answer for the following research questions (RQ).

    RQ1: Is the prevalence of obesity in Romania different from Europe?

    RQ2: Are there any differences in the prevalence of obesity in Romania when broken down by population, geographical regions, age or gender?

    RQ3: What is the potential level of the annual financial burden of obesity in Romania?

  3. Data analysis

    Before answering these research questions, we have to analyze the data within an international context. Unfortunately, data on each category of obesity is not available on Eurostat (2015). Thus, an international comparison regarding SO and SEO cannot be performed. Even so, under the assumption that the distribution of SO and SEO has good chances to be quite similar to OB ones, we present the situation of obesity at the European level in Figure 1.

    As one can observe, Romania registered the best situation within all the EU countries involved within EHIS. The share of people over 18 years who were obese (OB) ranges between 7.6% (for male) and 8.0% (for female). It is important to state that Romania is the only country in the list with an OB share lower than 10%. The worse situation was registered in Malta (22.9%). Moreover, there are plenty of Eastern European countries (Hungary, Estonia, Latvia, and Czech Republic) with higher registered values compared to Western European countries (France, Spain, Belgium).

    In Romania, the share of people over 18 years who were severely obese (SO) or extremely severely obese (SEO) nationwide was 1.5%, representing almost 260,000 people in absolute value. This value should raise awareness in Romania as socio-economic impacts of SO and SEO cannot be neglected, knowing that the financial effort induced by treatment increases geometrically (Mora, Gil and Sicras-Mainar, 2014) with the inclusion of the patients in the category SO or SEO. Unlike other countries like USA, Germany, where the share of the SO or SEO population is located at a level higher than 6% (Sturm, 2007 or Palmo, 2013), Romania has a much better position yet. This level of prevalence of SO and SEO was not evenly...

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