Lifestyles, health expenditure and the production of healthcare: Evidence from Greece

doi:10.21203/rs.3.rs-4659101/v1

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Lifestyles, health expenditure and the production of healthcare: Evidence from Greece

https://doi.org/10.21203/rs.3.rs-4659101/v1

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This study examines the determinants of health outcomes in Greece, with a focus on life expectancy at birth from 1988 to 2022. We model a production function where life expectancy is influenced by health expenditure and behavioral risk factors such as sugar, tobacco, and fat consumption. Using regional data analysis, we explore the relationship between health spending and various risky behaviors.

Our findings show that health expenditure significantly impacts health outcomes. Furthermore, sugar and tobacco consumption exhibit adverse effects on life expectancy, whereas fat consumption appears to have no influence. While on a national level, healthcare expenditure can lead to improvements in health outcomes, a deeper analysis at the regional level shows that this expenditure is driven by unhealthy consumption patterns. Hence, the relationship on the national level partially originates from unhealthy lifestyle choices. This leads to the conclusion that increases in healthcare expenditure do not necessarily enhance health outcomes proactively but rather mitigate the negative effects of unhealthy consumption, leading to increases in life expectancy.

These empirical insights underline the importance of policy intervention to promote a shift towards less risky alternatives. Encouraging the adoption of reduced-sugar or sugar-free products, as well as alternative options like e-cigarettes, emerges as a viable strategy for improving public health outcomes in Greece.

Life expectancy

Health care production

Health expenditure

Sugar

Tobacco

Vaping

The last few decades have seen significant growth in health expenditure across countries. Between 1960 and 2007, healthcare spending in OECD countries increased from an average of 3.8–9.0% of GDP. Different factors underpinning this growth have been identified. This includes the role of health income, as well as revisiting economic theories such as Baumol's (1967) cost disease theory, which relates to the low productivity of the health sector [1]. An alternative explanation for the rise in health spending posits that over time, individuals tend to seek and receive higher-quality healthcare [2]. The debate persists on whether, all else being equal, increased health spending translates into improved health outcomes. Several empirical studies support the notion of a flat curve of healthcare expenditure, suggesting that increased spending may not significantly impact health outcomes [2–4]. In contrast, some studies, such as research by Baicker and Chandra, even identify a negative association between measures of health quality and health spending [5]. Jones (2002) formalizes and empirically tests a model where health expenditure and life expectancy are endogenous variables driven by technological progress [6]. He finds little association between changes in life expectancy and changes in health expenditure (as a percentage of GDP) in the US. However, notably, a substantial portion of the increase in health spending over time is attributed to medical advancements.

While healthcare costs continue to rise, morbidity is rising, so better understanding of healthcare costs caused by different risk factors and health outcomes is important to promote public health. In this study, we investigate whether health productivity is directly linked to behavioral risk factors such as tobacco consumption, fat intake, and sugar consumption.

This article is structured as follows: Section 2 offers a comprehensive review of the literature on the determinants of life expectancy. Section 3 discusses research design, namely data and empirical methods. Section 4 presents empirical results while Section 5 discusses findings and acknowledges limitations. Finally, Section 6 concludes with some remarks about policy implications.

Shaw et al. (2005) explore the geographic distribution of life expectancy at ages 40 and 65 across 19 OECD countries in 1997, considering factors such as income, health expenditure, pharmaceutical spending, and lagged risk factors [7]. Their analysis reveals a positive association between health spending and life expectancy, challenging the notion of a flat cost curve. Additionally, they observe a positive impact of pharmaceutical expenditure on life expectancy across age groups, although this effect is influenced by population age distribution. Schoder and Zweifel (2009) investigate life expectancy inequality within countries, constructing a Gini coefficient for life span distribution based on OECD health data spanning from 1960 to 2004 [8]. They find that both medical and non-medical inputs negatively affect the distribution's second moment, supporting the hypothesis of a flat cost curve in the light of diminishing marginal productivity. Akkoyunlu et al. (2009) tackle spurious correlation issues in health production by employing a conditional error correction model for life expectancy, using the bounds testing procedure. Their analysis on the US reveals a significant relationship between life expectancy, pharmaceutical innovation, and public health care expenditure [9]. Crémieux et al. (1999, 2005) explore the relationship between health expenditure and outcomes in Canadian provinces, discovering that lower spending correlates with increased infant mortality and decreased life expectancy [10–11]. Papageorgiou et al. (2007) study the impact of medical innovation diffusion on life expectancy and mortality across 63 countries from 1961 to 1995. They find that technology diffusion significantly influences long-term averages of life expectancy and mortality in "non-frontier" countries [12]. Hall and Jones (2007) take a different approach, developing an economic model to explain the relationship between health spending and the value of life. Their analysis, focusing on the US, calculates the marginal cost of life-saving interventions across ages and time, suggesting that the observed increase in health spending may be attributed to the growth in this cost over time [13].

Furthermore, literature examines the effects of high-risk products such as tobacco, alcohol, sugar, and fat on life expectancy at the country level reveals a complex and significant impact on public health. Various studies highlight how these products contribute to mortality and affect life expectancy across different regions and demographics.

From 1980 to 2010, Rentería et al. (2016) explored the global impact of smoking, discovering that it accounts for about 20% of adult mortality in the countries studied. A pronounced increase in tobacco-related mortality was observed among women and in middle-income countries. They noted that eliminating smoking-related deaths could increase life expectancy by an average of 2.4 years for men and 1 year for women [14]. In a separate study, Sakata et al. (2012) examined the consequences of smoking within a large Japanese cohort, finding that early smokers experienced doubled mortality rates and a reduction in life expectancy by nearly a decade compared to non-smokers. The study emphasized that quitting smoking before age 35 could significantly mitigate these risks, underscoring the importance of early cessation [15]. Mackenbach et al. (2019) conducted an international comparative analysis across 15 European countries, focusing on how various risk factors contribute to life expectancy disparities. The study identified smoking, high body weight, and low income as major factors widening the life expectancy gap across educational levels. Smoking was the most significant risk factor among men, while high body weight and low income were more consequential for women [16]. Janssen et al. (2021) explored the combined effects of smoking, obesity, and alcohol on life expectancy trends in Europe from 1990 to 2014. Their research highlighted significant gender differences, with the combined impact of these lifestyle factors decreasing among men due to reductions in smoking-related mortality, while it increased among women due to rising mortality from all three factors. The study concluded that life expectancy trends would have been more stable without the adverse effects of these lifestyle factors [17]. The effects of sugar consumption on life expectancy are influenced significantly by dietary context and overall caloric intake. In regions like the USA, negative impacts such as increased coronary risk emerge only when sugar consumption substantially exceeds dietary guidelines [18–19]. In Italy, where sugar intake is generally lower, no direct correlation exists between sugar consumption and increased coronary risk or obesity [20]. Therefore, while excessive sugar consumption can contribute to health risks associated with shorter life expectancy, particularly in contexts of high intake, its impact varies and depends on overall dietary patterns and caloric balance. Poli et al. (2019) emphasize the complexity of the impact of fat consumption on life expectancy, challenging the prevailing notion that saturated fats have uniformly negative effects on cardiovascular health. They point to recent studies suggesting that general dietary recommendations advocating for low intake of saturated fats may not be fully supported by current research [20]. Furthermore, Poli et al. (2019) establish that the Mediterranean diet, especially its components such as olive oil, could have positive or at least neutral effects on health outcomes. The study underscores that despite traditionally critical views on fat consumption, the types of fats found in the Mediterranean diet might offer protective benefits against cardiovascular diseases and contribute to increased longevity [20].

Together, these studies illustrate the critical need for comprehensive public health policies that effectively manage the consumption of high-risk products to enhance life expectancy and reduce health disparities globally.

We use two comprehensive datasets to examine the interplay between healthcare outcomes, expenditure, and the consumption of unhealthy goods in Greece. Our first dataset encompasses country-level data, providing a macro lens on behavioral risk factors and their impact on life expectancy. The dataset comprises annual records for Greece spanning from 1988 to 2022. It includes variables such as life expectancy at birth and inflation-adjusted healthcare expenditure, both sourced from the OECD [21–22]. Additionally, it contains data on average daily caloric intake from fat and sugar, provided by the Food and Agriculture Organization (FAO) [23], along with smoking prevalence figures obtained from the World Bank [24], see Table 1.

Table 1

Greece county-level data for time 1988–2022
Variable	Description	Count	Mean	Std. Dev.
Life Expectancy	Life expectancy at birth, overall, in years [29]	62	77.17	3.08
Healthcare Expenditure	Logarithm of total health expenditures per capita (PPP dollars, deflated) [30]	35	1,354.78	319.41
Fat	Daily caloric intake that comes from fat [31]	60	1,197.92	178.11
Sugar	Daily caloric intake that comes from sugar [31]	61	267.59	51.66
Smoking Prevalence	Adult smoking prevalence (Age 15+) [32]	7	40.96	8.20
Employing this dataset, we constructed a regression model at the national level to investigate life expectancy's responsiveness to healthcare expenditure and the consumption of fats, sugars, and tobacco:

$$\:Life\:Expectanc{y}_{t}=\:\alpha\:+\beta\:\text{*}ln{\left(Healthcare\:expenditure\right)}_{t}+\gamma\:\text{*}{\text{Fat}}_{t}+\delta\:\text{*}{\text{Sugar}}_{t}+\:\theta\:\text{*}{\text{Smoking\:prevalence}}_{t}+{\epsilon\:}_{t}$$

where $\:Life\:Expectanc{y}_{t}$ is the life expectancy at birth in year t, and $\:ln\left(Healthcare\:expenditure\right)$ represents the natural logarithm of the national expenditure on healthcare. The regression coefficients $\:\gamma\:,\delta\:,\:and\:\theta\:$ measure the marginal impact of each category of unhealthy goods on life expectancy, $\:{\epsilon\:}_{t}$ is the error term.

The second dataset in this study is the Greek Household Budget Survey (HBS) [25], conducted annually to compile comprehensive consumption data from a representative cross-section of Greek households (Table 2). The HBS contains information on household spending habits on a wide array of goods, as well as specific purchase volumes for food, beverages, tobacco, and fuel. Despite its initiation in 2008, regional breakdowns for Greece's thirteen administrative regions ^[1] became available only in 2014, delineating our investigative period to the subsequent nine data releases. Due to this timeframe, our regional analysis mainly captures short and medium-term trends rather than long-term trends captured by the country-level analysis above.

However, this timeframe circumvents the profound repercussions of the 2008 financial crisis on Greek household spending which plummeted by about one-third in the years after the crisis. According to the Hellenic Statistical Authority, household spending has not yet recovered to pre-crisis levels and in 2022 was at approximately 75 percent [26]. Although spending showed a downward trend until 2016, indicators after 2012 suggest a stabilization, providing a baseline for examining the relationship between lifestyle choices and health expenditure in a relatively stable economic climate. Therefore, our timeframe from 2014 to 2022 provides a more stable view of spending behaviors than a longer timeframe would offer.

Our analytical approach intertwines regional data on outpatient healthcare services and comprehensive household expenditure with detailed accounts of regional purchases for selected consumables such as milk and cheese, oil and fat, juices, syrups and concentrates, sweet food, and tobacco. To counteract inflationary distortions and facilitate temporal parity, we've normalized all expenditure figures to the 2020 price benchmark using the Consumer Price Index (CPI), ensuring that our comparative analysis remains unaffected by the changing value of currency.

Table 2

HBS Regional data 2014–2022 [6]
Variable	Description	Count	Mean	Std. Dev.
Healthcare Expenditure	Outpatient services per household in euro	117	29.14	8.34
Total Household Expenditure	Expenditure per household in euro	117	1,640.68	202.79
Milk and Cheese	Consumption per household in grams, including: whole milk, low fat milk, milk preserved, yoghurt, cheese, other milk	117	14,573.88	2,917.28
Oil and Fat	Consumption per household in grams, including: butter, other vegetarian fat, olive oil, other oil and other fat	117	3,832.45	1,429.42
Juices, Syrups and Concentrates	Consumption per household in ml, including: fruit juices, like apple, pineapple etc. including mixed juices (fruit and vegetables), syrups and concentrates	117	2,143.78	705.97
Sweet Food	Consumption per household in grams, including: sweet pastry, sugar, jams, chocolate, confectionery, ice cream, fruit juices and soft drinks	117	3,008.40	593.27
Tobacco	Consumption per household in sticks, including: cigarettes, cigars and other tobacco	117	205.22	62.16

Examining national consumption habits reveals considerable variations across regions (see Appendix). For instance, Northern Greece consumes significantly more milk and cheese than Southern Greece. Conversely, the Peloponnese region consumes the least amount of sweet foods, while East Macedonia and Thrace, along with Crete, consume substantially more than the national average. These trends also extend over time; for example, milk and cheese consumption in Western Greece decreased by nearly half in 2022 compared to 2014. Similarly, there has been a notable increase in the consumption of sweet drinks in the Ionian Islands, where consumption has almost doubled from 2014 to 2022.

Using the regional granularity of the HBS data, we apply a fixed effects regression model with the following specification to assess the relationship between households' outpatient healthcare spending and their consumption patterns, specifically consumption of milk and cheese, oil and fat, juices, syrups and concentrates, sweet food, and tobacco:

$$\:Outpatient\:Healthcare\:Expenditur{e}_{it}=\:\alpha\:+\beta\:\:\text{*}\:\text{l}\text{n}{\left(Total\:Household\:Expenditure\right)}_{it}+{\gamma\:}_{1}\text{*}{\text{Milk\:and\:Cheese}}_{it}+{\gamma\:}_{2}\text{*}{\text{Oil\:and\:Fat}}_{it}\:+{\delta\:}_{1}\text{*}{\text{Juices,\:Syrups\:and\:Concentrates}}_{it}+\:{\delta\:}_{2}\text{*}{\text{Sweet\:Food}}_{it}+\:\theta\:\text{*}{\text{Tobacco}}_{it}+\tau\:\:\text{*}\:{\text{Y}\text{e}\text{a}\text{r}}_{\text{t}}\:+{\epsilon\:}_{it}$$

where $\:{\text{O}\text{u}\text{t}\text{p}\text{a}\text{t}\text{i}\text{e}\text{n}\text{t}\:\text{H}\text{e}\text{a}\text{l}\text{t}\text{h}\text{c}\text{a}\text{r}\text{e}\:\text{E}\text{x}\text{p}\text{e}\text{n}\text{d}\text{i}\text{t}\text{u}\text{r}\text{e}}_{it}$ is the amount of money an average household in region $\:i$ and year $\:t$ spends on outpatient healthcare services. $\:ln{\left(Total\:Household\:Expenditure\right)}_{it}$ represents the natural logarithm of the regional total household expenditure with $\:\beta\:$ measuring the impact of an increase in household expenditure in a region on regional healthcare expenditure. The regression coefficients $\:\gamma\:,\delta\:,\:and\:\theta\:$ measure the marginal impact of each category of unhealthy goods on health care expenditure, $\:{\epsilon\:}_{it}$ is the error term.

In a nutshell, in this paper we are conducting a dual analysis on the impact of lifestyle choices on health in Greece. Firstly, we perform a macro-level analysis of how Greece's life expectancy responds to healthcare expenditure and the consumption of fats, sugars, and tobacco. Secondly, we focus on a micro-level examination of households' outpatient healthcare spending in relation to their consumption of milk and cheese, oils and fats, juices, syrups and concentrates, sweet foods, and tobacco. This dual approach provides us with a detailed view of the health outcomes of lifestyle choices in Greece.

With the country-level regression we first aim to explore the relationship between consuming unhealthy goods and healthcare outcomes in Greece (Table 3). As a proxy for the overall health of the country’s population we use life expectancy at birth as the dependent variable in the regression. We control for total household expenditure in Greece, while our main independent variables are the sugar and fat consumed by an average person as well as the smoking prevalence.

Table 3

Country-level regression output
Variable	Estimate		t-value	p-value
Intercept	79.832	4.094	19.500	0.000***
Log(exp)	1.883	0.448	4.205	0.000***
Fat	-0.003	0.003	-1.038	0.308
Sugar	-0.009	0.003	-2.773	0.010**
Tobacco	-0.158	0.014	-11.453	0.000***
Multiple R-squared: 0.937, Adjusted R-squared: 0.929, F-statistic: 108.4 on 4 and 29 DF, p-value: < 0.001

Our regression analysis uncovers a significant and positive correlation between healthcare expenditure and life expectancy in Greece, suggesting that increased investment in healthcare could further augment Greeks' life expectancy. The effect of an additional percent of health spending is estimated to be about 0.018 years of life expectancy, suggesting a strong impact of health investments. However, since we are observing a relatively long time period, diminishing returns may lead to a weaker contemporary relationship than the one shown in our regression. This aligns with the findings of Shaw et al. (2005), who observed a positive association between health spending and life expectancy across OECD countries as well as the research conducted by Akkoyunlu et al. (2009) in the United States [7, 9]. Complementing these findings, Crémieux et al. (1999, 2005) discovered a corresponding trend in Canadian provinces, where reduced health spending was associated with adverse health outcomes [10–11]. Moreover, our study reaffirms the detrimental effects of sugar and tobacco on life expectancy, with both showing significant negative relationships. This aligns with research that associates excessive consumption of these goods with various health issues [14, 16, 18–18].

Interestingly, our analysis does not reveal a significant impact of fat consumption, such as olive oil or cheese, on life expectancy. This finding, while initially surprising, aligns with and lends support to the conclusions drawn by Poli et al. (2018), who suggest that the Mediterranean diet may confer beneficial effects on health [20]. It prompts further investigation, considering the Mediterranean diet's reputation for health benefits, which indicates there could be potential protective factors at play or areas for refinement in our model.

These results collectively underscore the adverse effects of unhealthy consumption on health outcomes in Greece, contrasted by the beneficial impact of healthcare expenditure. However, this raises a critical question: Does healthcare spending directly enhance health outcomes, or does it merely offset the consequences of poor lifestyle choices? In a scenario dominated by treatable diseases resulting from unhealthy consumption, healthcare expenditure's role appears compensatory rather than fundamentally curative.

Lacking the exogenous variation necessary for disentangling these effects, we turn to the HBS dataset's regional variation. This approach aims to scrutinize if patterns in unhealthy consumption correlate with heightened healthcare spending. The forthcoming analysis (see Table 4) seeks to validate the hypothesis that lifestyle choices significantly burden healthcare resources, emphasizing the necessity of targeted public health interventions.

Table 4

Regional-level regression output
Variable	Estimate		t-value	p-value
Intercept	788.383	549.558	1.435	0.151
Ln(Total Household Expenditure)	20.370	6.267	3.250	0.001***
Milk and Cheese	-0.000	0.000	-0.489	0.625
Oil and Fat	-0.001	0.001	-0.384	0.701
Juices, Syrups and Concentrates	0.003	0.001	1.957	0.050*
Sweet Food	-0.001	0.001	-1.165	0.244
Tobacco	0.021	0.012	1.698	0.089
Year	-0.391	0.272	-1.435	0.151
Multiple R-squared: 0.419, Adjusted R-squared: 0.382, F-statistic: 20.80 on 7 and 109 DF, p-value: < 0.001
Notes: [1] Regional fixed effects [2] Standard Errors are robust to cluster correlation (cluster)

Utilizing the HSB dataset’s detailed product categorization, our second regression analysis dissects sugar and fat into finer subcategories, diverging from the aggregated approach in the national-level assessment. Despite this granular scrutiny, the consumption of fatty foods once again shows no significant correlation with healthcare expenditure. In contrast, a noteworthy and significant relationship emerges for both tobacco use and the intake of juices, syrups, and concentrates, underscoring an increase in healthcare spending with higher consumption of these products.

These findings substantiate the premise that healthcare expenditure is, to a degree, a compensatory response to the health detriments of certain lifestyle choices. Viewing this from another perspective, it highlights the potential for substantial healthcare savings through the promotion of healthier living habits and the reduction of tobacco and sugary product consumption.

An analysis of the Global Burden of Disease Study 2016 estimated the effects of risk factors on health effects in Greece [27]. Elevated BMI, smoking and unhealthy diet are responsible for much of the excess mortality compared to Cyprus and western Europe. Another study by Economou & Giorno, although in 2009, confirms that a growing share of the Greek population tend to adopt unhealthy eating habits contributing to high morbidity and mortality rates[28]. Risk-factors also impact hospital admissions. The study conducted by Tsalapati et al., (2014) shows that Greek smokers cause 199,000 hospital admissions annually [29].

The implications of our results extend beyond individual health outcomes to inform broader public health strategies. Considering the significant impact of tobacco and sugary liquids on healthcare costs, targeted interventions aimed at curbing their consumption could serve as effective levers for health improvement and fiscal sustainability. Further exploration into the efficacy and cost-benefit ratios of such preventative measures, as evidenced by the literature, would bolster the case for their adoption in public health policies.

Our study yields two principal insights. First, we investigated the determinants influencing health outcomes in Greece, focusing particularly on life expectancy from 1988 to 2022. Our results demonstrate that the consumption of unhealthy substances, specifically sugar and tobacco, is associated with adverse health effects. Interestingly, fat consumption shows no significant impact on these outcomes. Second, we utilized regional household data on expenditure and volumes of goods using the Greek Household Budget Survey (HBS) covering 2014–2022. Our analysis reveals that at the regional level, healthcare expenditure is driven by unhealthy consumption patterns. This is confirmed by the adverse effects of sugar-sweetened beverages (SSBs) and tobacco consumption on healthcare expenditures at the household level, substantiating our regression results.

These findings lead to the conclusion that increases in healthcare expenditure do not necessarily enhance health outcomes proactively but rather mitigate the negative effects of unhealthy consumption, contributing to increases in life expectancy and supporting the notion of a flat cost curve [2–4]. Our findings suggest that reductions in unhealthy consumption could amplify beneficial effects on life expectancy more than increases in healthcare spending alone.

Reducing harmful consumption brings not only health benefits but also economic effects. Our findings suggest that Greek households could potentially reduce their annual healthcare expenditures by approximately 270 million euros if they either halved their consumption of sugar and tobacco or substituted these with less harmful alternatives. Considering the average duration of smoking among Greeks, which is notably high at 20.7 years for men and 14.1 years for women [3849], reducing tobacco consumption or switching to less harmful products could result in up to 2.0 billion euros in household savings over time. Since there is no specific duration for sugar consumption, we estimate this figure using the average age and life expectancy in Greece. Here, households could save 4.7 billion euros in out-of-pocket healthcare expenditures.

Interestingly, these costs are not covered by health insurance or government expenditure but are directly linked to household budgets. In health economics, costs attributable to unhealthy consumption are typically estimated using direct healthcare expenditures and indirect costs, such as productivity losses due to sickness or premature death. However, these costs typically do not affect household budgets directly but are borne by society as a whole. We leave the estimation of these societal costs for further research.

This study is not without limitations. One key constraint is the potential for endogeneity between healthcare expenditures and unhealthy consumption behaviors, which could bias our results. Moreover, our analysis might not fully capture all confounding variables that influence both health outcomes and consumption patterns, such as socioeconomic factors and access to healthcare services. These factors warrant further investigation to elucidate the observed relationships more comprehensively.

A multifaceted health policy approach is necessary to address the consumption of harmful products like sugary drinks and tobacco. This involves policy measures aimed at reducing consumption, promoting healthier alternatives, and ultimately improving public health outcomes. Among possible policies to be implemented, increasing taxes on products that are known to be more harmful to health can serve as a powerful deterrent to their consumption. The rationale for this policy is twofold. First, it makes these products less financially accessible or attractive to consumers, especially to younger demographics who are more price-sensitive. Second, it signals to the population that not all products are created equal, so to speak. More costly products, in this case, are more expensive because of the higher externalities weighing on society as a result of their consumption. As a result, taxation creates a direct link between toxicity and price that helps the decisions of the consumers. Third, the revenue generated from such taxes can be reinvested into public health initiatives.

Over 50 countries worldwide have implemented some form of tax on SSBs as a strategy to curb consumption. In regions such as South Asia and Latin America, a significant proportion of the population is covered by SSB taxes to improve public health and generate revenue [30–31].

A clear example of such logic is in tobacco product taxation, which requires careful nuancing to effectively address public health concerns. Given the peculiarities of tobacco, this field offer learnings that can be used as good (or bad) practices for other products. Firstly, a harm-based taxation strategy is essential, where traditional cigarettes and other combustible products (such as fine-cut), which pose the highest health risks, are taxed the most heavily. This ensures that less harmful alternatives, such as e-cigarettes and heated tobacco products (HTPs), are taxed less, thus incentivizing individuals who are unable or unwilling to quit smoking to switch to these safer options.

Secondly, the tax rates on traditional tobacco products need to be harmonized. In Greece, although there is a tax differential between combustible products and reduced-risk products, there is also a discrepancy between taxes on factory-made cigarettes and fine-cut tobacco. This is illogical. While these are defined (in a rather manipulative way) as two different products by the industry, the truth of the matter is that both of them end up being the same product in their conclusive form, that is, cigarettes consumed by smokers. This inconsistency reduces the incentive to switch to less harmful products and also makes traditional smoking more affordable, undermining public health objectives.

Thirdly, tobacco taxes must be adjusted for inflation annually. Since the last adjustment in 2017, the real cost of smoking in Greece has effectively decreased each year, making cigarettes more affordable over time and lessening the financial deterrent intended by taxation.

It is important to acknowledge that while risk-reduced products such as e-cigarettes and HTPs are considered less harmful than traditional cigarettes, they are not risk-free. Any policy promoting these alternatives should include educational initiatives about their risks and proper usage. [32–33].

Relying solely on taxation as a strategy may not be sufficient to induce significant behavioral changes. A comprehensive approach that combines fiscal measures with education and regulatory policies is necessary to effectively reduce unhealthy consumption and promote public health.

Other regulatory measures play a critical role in both spheres. For sugary drinks, this could include limiting the availability of these beverages in schools and public institutions, limiting the maximum allowable sugar content, and mandating clear labeling of sugar content on product packaging. For tobacco, beyond taxation and the promotion of less harmful alternatives, regulations could enforce stricter packaging and advertising guidelines for more damaging products, restrict sales channels, and implement smoking bans in public areas to reduce secondhand smoke exposure.

In addition to taxation and regulation, public awareness campaigns are crucial. These campaigns should not only highlight the risks associated with consuming high-sugar products and tobacco but also promote healthier lifestyle choices. For sugary drinks, advertisements and public messaging could emphasize the health risks of excessive sugar consumption, such as obesity, type 2 diabetes, and heart disease. The message should be clear: reducing sugar intake is a crucial step toward living a longer, healthier life. In Greece, public awareness campaigns on sugary drinks are not as extensive as in countries like the UK, where public health campaigns are common. Change4Life, for example, has engaged communities through media and school programs to reduce sugar intake [35]. The WHO also emphasizes the importance of such campaigns, suggesting that raising taxes on sugary drinks, combined with public awareness campaigns, can significantly reduce consumption, and improve public health outcomes [36]. Campaigns and policies rolled out in the UK and in parts of the USA have led to measurable decreases in sugary drink consumption, particularly among children and adolescents [37–38]. They often use a variety of media and community engagement strategies to educate the public and promote responsible consumption. Overall, the effectiveness of public awareness campaigns can greatly enhance the impact of fiscal policies.

The same awareness should be created in tobacco. it is essential to implement public awareness campaigns similar to those used in the UK, which focus on cessation and educating the public about less harmful alternatives. Campaigns such as "Swap to Stop," "Stoptober," "No Smoking Day," and seasonal prompts during Ramadan and the New Year are designed to facilitate quitting or transitioning to reduced-risk products such as e-cigarettes and heated tobacco products (HTPs) [38–39]. These campaigns should provide clear, scientifically-backed information that encourages smokers to either quit or switch to these alternatives, which are considered less harmful under strict regulatory standards.

In Greece, the support for such health claims about reduced-risk tobacco products is structured through a scientific evaluation system established by Law 4715/2020 [40]. This law outlines a stringent procedure for the communication of reduced-risk messages, which must be assessed and approved by a specialized committee. The system ensures that claims about the reduced health risks of new tobacco products are scientifically substantiated, thereby enabling their consideration within regulatory processes.

By adopting a framework similar to the UK, Greece can enhance public understanding and support for smoking cessation and the adoption of safer alternatives, ultimately contributing to better public health outcomes.

In conclusion, tackling the public health challenges posed by sugary drinks and tobacco requires a comprehensive strategy that includes taxation, education, promotion of healthier alternatives, and stringent regulatory measures. Such a multifaceted approach acknowledges the complexity of changing consumer behavior and addresses the issue from multiple angles to maximize the impact on public health. By implementing these policies, policymakers can significantly contribute to the reduction of non-communicable diseases and enhance the overall health and wellbeing of the population.

No funding was received for conducting this study. The author has no relevant financial or non-financial interests to disclose

Data availability (data transparency): The dataset used in this study are included in this published article (pls see references 21-26 for all datasets links). Example from the Hellenic Statistical Authority at https://www.statistics.gr/en/statistics/-/publication/SFA05/2022

Code availability (software application or custom code): Not applicable

Authors' contributions: single contributor for this manuscript

Baumol WJ. Macroeconomics of unbalanced growth: the anatomy of urban crisis. Am Econ Rev. 1967;57:415-26.
Skinner J, Fisher E, Wennberg JE. The efficiency of Medicare. In: Wise D, editor. Analyses in the economics of aging. University of Chicago Press and NBER; 2005. p. 129-57.
Fisher ES, Wennberg D, Stukel T, Gottlieb D, Lucas FL, Pinder EL. The implications of regional variations in Medicare spending Part 2: health outcomes and satisfaction with Care. Ann Internal Med. 2003;138:288-99.
Fisher ES, Bynum JP, Skinner JS. Slowing the growth of health care costs—lessons from regional variation. New Engl J Med. 2009;360:849-52.
Baicker K, Chandra A. The productivity of physician specialization: evidence from the Medicare program. Am Econ Rev. 2004;94(2):357-61.
Jones C. Why have health expenditures as a share of GDP risen so much? NBER working paper no. 9325; 2002.
Shaw J, Horrace W, Vogel R. The determinants of life expectancy: an analysis of the OECD health data. South Econ J. 2005;71:768-83.
Schoder J, Zweifel P. Flat-of-the-curve medicine—a new perspective on the production of health. Working paper no. 0901. University of Zurich, Zurich; 2009.
Akkoyunlu S, Lichtenberg F, Siliverstovs B, Zweifel O. Spurious correlation in estimation of the health production function: a note. Econ Bull. 2009;30:2505-14.
Crémieux P-Y, Ouellette P, Pilon C. Healthcare spending as determinants of health outcomes. Health Econ. 1999;8:627-39.
Crémieux P-Y, Mieilleur M-C, Ouellette P, Petit P, Zelder P, Potvin K. Public and private pharmaceutical spending as determinants of health outcomes in Canada. Health Econ. 2005;14:107-16.
Papageorgiou C, Savvides A, Zachariadis M. International medical technology diffusion. J Int Econ. 2007;72:409-27.
Hall R, Jones C. The value of life and the rise in health spending. Q J Econ. 2007;122:39-72.
Rentería E, Jha P, Forman D, et al. The impact of cigarette smoking on life expectancy between 1980 and 2010: a global perspective. Tobacco Control. 2016;25:551-57.
Sakata R, McGale P, Grant EJ, Ozasa K, Peto R, Darby SC. Impact of smoking on mortality and life expectancy in Japanese smokers: a prospective cohort study. BMj. 2012;345.
Mackenbach JP, Valverde JR, Bopp M, Brønnum-Hansen H, Deboosere P, Kalediene R, et al. Determinants of inequalities in life expectancy: an international comparative study of eight risk factors. The Lancet Public Health. 2019;4(10):e529-e537.
Janssen F, Trias-Llimos S, Kunst AE. The combined impact of smoking, obesity and alcohol on life-expectancy trends in Europe. International Journal of Epidemiology. 2021;50(3):931-41.
Tasevska N, Pettinger M, Kipnis V, et al. Biomarker-calibrated total sugars intake and risk of type 2 diabetes and cardiovascular disease in the Women’s health initiative observational study. Am J Epidemiol. 2018; https://doi.org/10.1093/aje/kwy115.
Yang Q, Zhang Z, Gregg EW, Flanders WD, Merritt R, Hu FB. Added sugar intake and cardiovascular diseases mortality among us adults. JAMA Intern Med. 2014;174:516-24. https://doi.org/10.100
Poli A, Agostoni C, Graffigna G, Bosio C, Donini LM, Marangoni F. The complex relationship between diet, quality of life and life expectancy: A narrative review of potential determinants based on data from Italy. Eating and Weight Disorders-Studies on Anorexia, Bulimia and Obesity. 2019;24:411-19.
OECD. Life expectancy at birth. [Internet]. 2024 [cited 2024 Apr 17]. Available from: https://data.oecd.org/healthstat/life-expectancy-at-birth.htm
OECD. Health expenditure and financing. [Internet]. 2024 [cited 2024 Apr 17]. Available from: https://stats.oecd.org/Index.aspx?DataSetCode=SHA
Food and Agriculture Organization of the United Nations. FAOSTAT. [Internet]. 2024 [cited 2024 Apr 17]. Available from: https://www.fao.org/faostat/en/#data/FBS and https://www.fao.org/faostat/en/#data/FBSH
The World Bank. Prevalence of current tobacco use (% of adults) – Greece. [Internet]. 2024 [cited 2024 Apr 17]. Available from: Prevalence of current tobacco use (% of adults) - Greece | Data (worldbank.org)
Hellenic Statistical Authority. Household Budget Survey (after 2008). Retrieved April 17, 2024, from https://www.statistics.gr/en/statistics/-/publication/SFA05/2022
Hellenic Statistical Authority. Household Budget Survey 2022 [Internet]. Piraeus: Hellenic Statistical Authority; 2023 Sep 28
Global Burden of Disease Study 2016. The burden of disease in Greece, health loss, risk factors, and health financing, 2000–16: an analysis of the Global Burden of Disease Study 2016. Lancet Public Health. 2018;3(8):E395-E406.
Economou C, Giorno C. Improving the performance of the public health care system in Greece. OECD Economics Department Working Papers No. 722; 2009.
Tsalapati K, et al. Going up in ashes? Smoking-attributable morbidity, hospital admissions and expenditure in Greece. Eur J Public Health. 2014;24(3):477-9.
Global Food Research Program. Taxes on unhealthy foods and beverages [Internet]. 2023 [cited 2024 Apr 17]. Available from: https://www.globalfoodresearchprogram.org/resource/taxes-on-unhealthy-foods-and-beverages/
Obesity Evidence Hub. Countries that have implemented taxes on sugar-sweetened beverages (SSBs) [Internet]. 2024 [cited 2024 Apr 17]. Available from: https://www.obesityevidencehub.org.au/collections/prevention/countries-that-have-implemented-taxes-on-sugar-sweetened-beverages-ssbs
McNeill A, Brose LS, Calder R, Bauld L, Robson D. Evidence review of ecigarettes and heated tobacco products 2018. A report commissioned by Public Health England. London: Public Health England; 2018.
Royal College of Physicians. Nicotine without smoke: tobacco harm reduction. London: RCP; 2016.
Wrieden WL, Levy LB. ‘Change4Life Smart Swaps’: quasi-experimental evaluation of a natural experiment. Public Health Nutr. 2016;19(13):2388-92.
World Health Organization. Sugar-sweetened beverages and childhood obesity [Internet]. 2014 [cited 2024 Apr 16]. Available from: https://www.who.int/tools/elena/bbc/ssbs-childhood-obesity
Elliott-Green A, Hyseni L, Lloyd-Williams F, Bromley H, Capewell S. Sugar-sweetened beverages coverage in the British media: an analysis of public health advocacy versus pro-industry messaging. BMJ Open. 2016;6(7):e011295.
Krieger J, Bleich SN, Scarmo S, Ng SW. Sugar-sweetened beverage reduction policies: progress and promise. Annu Rev Public Health. 2021;42:439-61.
Balogun, B., & Harker, R. (2023, October 16). The smokefree 2030 ambition for England. Research Briefing: Health Services. Retrieved from https://commonslibrary.parliament.uk/research-briefings/cbp-9655/
Nicolaou SA, Heraclides A, Markides KS, Charalambous A. Prevalence and social determinants of smoking in the adult Greek Cypriot population. Hippokratia. 2016 Oct-Dec;20(4):284-291. PMID: 29416301; PMCID: PMC5788227.
Greece. Law 4715/2020. Government Gazette 149 (1 August 2020)

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Lifestyles, health expenditure and the production of healthcare: Evidence from Greece

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1 Introduction

2. Literature Review

3. Research Design

4. Results

5. Discussion and Limitations

6. Policy Recommendations

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