Introduction

In nearly every region, suboptimal diet is the leading risk factor for poor health; hunger and malnutrition result in substantial burdens and contribute to the incidence and prevalence of noncommunicable diseases (NCDs) (Forouzanfar and others 2015; Lim and others 2012). Improving individual and population dietary habits needs to become a health system and public health priority (IFPRI 2015). In recent years, interventions have been evaluated to improve dietary habits, including individual-level interventions in the health system (for example, nutrition counseling); population-level interventions; and novel, technology-based interventions (for example, Internet- and mobile-based programs). A detailed discussion of these interventions is beyond the scope of this chapter. Here, we focus on dietary priorities and policies for global NCDs, including key dietary targets, current distributions of consumption, and ensuing health burdens. We summarize the evidence for effective population-level interventions to improve diet quality, and we discuss data gaps and needs for assessing cost-effectiveness.

The global effects of hunger and nutrient deficiencies have been recognized for more than a century, but the emergence of poor diet as a major cause of NCDs has been documented only in recent decades (Forouzanfar and others 2015; Lim and others 2012). Optimal responses to this global challenge have been slowed by several factors, including the relatively recent attention given to the science of diet and NCDs; a historical focus on isolated nutrients rather than foods and diet patterns; and an emphasis on diet-induced obesity (WHO 2012). These factors have led to the neglect of the far larger burdens of NCDs owing to nonobesity-related pathways. Modern nutritional science, originating in the early 20th century, focused on nutrient deficiency diseases, such scurvy, pellagra, and rickets. The initial recognition in the late twentieth century of the additional major effect of diet on NCDs led to nutrient deficiency paradigms being extended to the study of chronic diseases (Mozaffarian and Ludwig 2010). Nutrient deficiency diseases, however, are explicitly caused and can be prevented or treated by single nutrients. In contrast, NCDs arise from complex perturbations of food intakes and overall dietary patterns, including insufficiencies of specific healthful foods and excesses of unhealthful foods (Afshin and others 2014; Chen and others 2013; de Munter and others 2007; Imamura and others 2015; Kaluza, Wolk, and Larsson 2012; Micha, Wallace, and Mozaffarian 2010; Mozaffarian and Rimm 2006; Mozaffarian and others 2006).

The global obesity epidemic has appropriately focused attention on diet. However, adiposity is only one pathway of effect of diet on NCDs. Diet quality has an enormous effect on NCDs, in particular, cardiovascular diseases, independent of body weight or obesity. Although undernutrition is an appropriate term for caloric and nutrient deficiency, overnutrition is an incorrect corollary for NCDs and even obesity. The term fails to capture the complexity of poor food habits that cause NCDs: (1) inadequate ingestion of healthful foods; and (2) ingestion of foods created by suboptimal processing (for example, those rich in refined grains, starches, and sugars), foods prepared by modern methods (for example, high temperature commercial cooking), and foods containing additives such as trans fats and sodium. Accordingly, the appropriate term for the global epidemic of diet-induced NCDs is not overnutrition, but malnutrition: poor dietary quality or composition.

Dietary Risk Factors for Noncommunicable Diseases

Understanding the key dietary factors that have the strongest evidence of effect on NCDs, and the effective and cost-effective policies to address these factors, is essential to help guide public health planning and interventions. The Global Burden of Disease Study (GBD) of 2010 and 2013 systematically evaluated the evidence for effects of key foods, beverages, and nutrients on NCDs, including causal effects, optimal consumption levels for lowering risk, and current distributions of intakes worldwide (Forouzanfar and others 2015; Lim and others 2012; Micha and others 2012; Micha and others 2014; Micha and others 2015; Powles and others 2013; Singh, Micha, Khatibzadeh, Lim, and others 2015; Singh, Micha, Khatibzadeh, Shi, and others 2015).

Overall, consumption levels were suboptimal for each evaluated dietary risk factor on a global scale, but substantial diversity in consumption existed across regions and even neighboring countries (Micha and others 2104; Micha and others 2015; Mozaffarian and others 2014; Singh, Micha, Khatibzadeh, Lim, and others 2015; Singh, Micha, Khatibzadeh, Shi, and others 2015). For most dietary factors, the proportion of nations with average consumption levels meeting optimal intakes was low, typically representing less than 20 percent of the global adult population. Based on the 2010 GBD analysis, the five leading dietary contributors to death were as follows:

• Low fruits (4.9 million attributable deaths per year)
• High sodium (3.1 million)
• Low nuts and seeds (2.5 million)
• Low vegetables (1.8 million)
• Low whole grains (1.7 million).

In comparison, high sugar-sweetened beverage (SSB), low milk, and high red meat intakes had lower estimated mortality burdens at 184,000; 101,000; and 38,000 attributable deaths per year, respectively. These findings highlight the particular relevance of malnutrition rather than overnutrition. This evidence contrasts with conventional dietary priorities to reduce NCDs, which have traditionally focused on unhealthful factors such as saturated fat, sodium, red meats, SSBs, and added sugars. Reductions in these factors are important. However, such reductions would have a relatively small effect on overall NCD burdens compared with a coordinated strategy that increases intakes of healthful foods.

The 2010 and 2013 GBD studies focused not only on foods, beverages, and nutrients with probable or convincing evidence of effect on NCDs, but also on available global evidence on their consumption levels (table 6.1). Because of a lack of available global data, certain dietary factors such as refined carbohydrates and dairy foods beyond milk could not be included. Refined carbohydrates include white rice, bread, most breakfast cereals, added sugars, and starches such as white potatoes. Refined carbohydrates are clearly relevant for NCDs, with clear links to greater weight gain (Mozaffarian and others 2011; Te Morenga, Mallard, and Mann 2013), diabetes, and coronary heart disease (CHD) (Mozaffarian 2014). Recent global policy efforts focus on added sugars, especially SSBs. SSBs are clearly adverse for weight gain and cardiometabolic health (Mozaffarian and others 2011; Pan and Hu 2011) and are particularly heavily consumed by youth and younger adults. A general focus on reducing all refined carbohydrates—not only added sugars—is warranted because of their adverse health effects (Dietary Guidelines Advisory Committee 2015).

Table 6.1

Global Consumption and Optimal Levels, Deaths, and Disability-Adjusted Life Years Attributable to Dietary Habits with Largest Public Health Effect, 2010.

Dairy foods are a major component of many diets; they are particularly relevant for sufficient protein, nutrients, and calories among the poorest populations. Their cardiometabolic effects, relevant bioactive characteristics (for example, fatty acids, probiotics, and fermentation), and potential effects by subtype (for example, milk, cheese, and yogurt) remain understudied. Current evidence supports guidelines for modest dairy consumption of two to three servings a day, in particular, yogurt and cheese (Aune and others 2013; Chen and others 2014). Conventional recommendations to select fat-reduced, rather than whole-fat, dairy are not strongly evidence based; according to current data, both appear to be reasonable choices (Mozaffarian 2014).

GBD 2010 and 2013 also did not systematically assess the cardiometabolic effects of flavonoid-rich foods, including cocoa, berries, apples, and tea. Although these appear potentially beneficial, the heterogeneity of specific phenolics, the variability of dietary sources, and fewer studies that evaluate clinical endpoints limit strong conclusions (Hooper and others 2012; Shrime and others 2011) but provide a strong basis for further investigation.

Effectiveness of Population Interventions to Improve Diet

Because of current and projected disease burdens, identifying and implementing effective interventions to improve diet quality needs to be a health system priority and public health priority for all regions. Behavior change interventions that target individuals with individualized nutrition counseling within the health system can be effective. However, these often have limited coverage, can be more costly, and may have limited sustainability (Artinian and others 2010; Rose 1985). In comparison, population-based interventions can have broader effect, lower cost, and greater sustainability, as well as the potential to reduce disparities (McGill and others 2015; Mozaffarian and others 2012). Such interventions include those implemented at health system, organizational (for example, schools and workplaces), community, state, and national levels. The evidence of effectiveness of such interventions has been systematically reviewed, including for education and mass media campaigns, food labeling and consumer information, food pricing and economic incentives, school and worksite interventions, and direct restrictions and mandates (Afshin, Penalvo, and others 2015; Mozaffarian and others 2012). Several effective policy strategies are listed in table 6.2.

Table 6.2

Evidence-Based Population Interventions to Improve Diet.

Fiscal Policies

Fiscal measures, including taxation and subsidies, are among the most promising dietary policies. These measures are recommended in the American Heart Association Scientific Statement on population interventions; by the United Nations Political Declaration on NCDs; and by the World Health Organization’s (WHO) Global Strategy on Diet, Physical Activity and Health (Mozaffarian and others 2012; UN 2011; WHO 2004). Cross-sectional price-elasticity analyses of demand (Andreyeva, Long, and Brownell 2009; Green and others 2013), evidence from prospective studies (Thow, Downs, and Jan 2014), and evidence from intervention studies (An 2013) demonstrate consistent efficacy of changes in food pricing, including subsidies to increase healthful foods and taxes to decrease unhealthful foods and drinks. The magnitude of the effect is proportional to the price change; larger changes of 10–50 percent have greater effect. Although small taxes are not expected to have a major effect on population consumption levels, such taxes are more politically feasible and can generate large amounts of revenue for other prevention programs. Fiscal approaches also have larger effects in low-income countries and on lower socioeconomic groups, the populations who are at highest risk and have the most to gain from improved diets (Green and others 2013).

Evidence from cross-sectional analyses of price elasticity of demand suggests that each 10 percent change in the price of foods and beverages is associated with a 4 percent to 8 percent change in consumption (table 6.3). Several factors may influence the magnitude of this effect, including the specific dietary target and national and individual socioeconomic status.

Table 6.3

Change in Demand for Major Food Groups per 10 Percent Change in Price of the Food Groups in Low-, Middle-, and High-Income Countries, 1990–2011. percent

We systematically evaluated and quantified the prospective effect of price changes on dietary consumption in 23 interventional and seven observational studies (Afshin, Del Gobbo, and others 2015). The interventional studies were conducted in five countries (France, the Netherlands, New Zealand, South Africa, and the United States), and the observational studies were conducted in the United States. Pooling all studies, we found that each 10 percent price decrease was associated with a 14 percent (95 percent confidence interval 11–17) increase in consumption of fruits and vegetables and a 16 percent (95 percent confidence interval 10–23) increase in consumption of other healthful foods. A 10 percent price increase was associated with 7 percent (95 percent confidence interval 3–10) lower consumption of SSBs and 3 percent (95 percent confidence interval 1–5) lower consumption of fast foods. The study also found that lower prices of fruits and vegetables were associated with lower body mass index (0.04 kilogram per square meter [kg/m²] per 10 percent price decrease [95 percent confidence interval 0.00–0.08 kg/m²]). Thus, price changes clearly influence consumption significantly. The effect on health can be modified by other factors, such as alternative choices (for example, a consumer’s selection of substitutes in response to reducing purchases of a taxed food or increasing purchases of a subsidized food) and food industry responses (for example, use of internal pricing strategies to reduce the effect of taxation).

Cost-Effectiveness of Population Interventions to Improve Diet

Cost is a key potential barrier to implementation and sustainability of any evidence-based intervention. Although based on the first principles that many population-level dietary interventions may be highly cost-effective or even cost saving, formal cost-effectiveness analyses in this area are limited (Cobiac, Veerman, and Vos 2013). Historically, this paucity of data results from lack of reliable data on dietary habits in many populations, insufficient systematically determined effect sizes of population-level interventions to improve diet, controversy over causal effects of dietary changes, and little systematically collected data on costs of such interventions. In recent years, efforts have been made to address these gaps. The 2010 and 2013 GBDs assess global consumption levels of a range of dietary factors by age and gender in 187 countries and the best evidence for their etiologic effects on NCDs. The WHO NCD Costing Tool provides data on health care costs in many countries, as well as resource ingredient needs and corresponding costs of selected policy interventions such as mass media campaigns and alcohol taxation (Evans and others 2005; Murray and others 2000; WHO 2003). For most policies, acquiring the data needed to estimate the cost of the intervention remains a challenge. Chapter 20 in this volume (Watkins, Nugent, and Verguet 2017) offers a detailed review of cost-effectiveness studies of dietary policies.

The early evidence that has emerged from evaluations of actual policies is mixed. In a short-term evaluation of the first city-level tax on SSBs in the United States, Cawley and Frisvold (2015) found relatively little pass through of the Berkeley, California, SSB tax to consumers; retail prices rose by less than half of the amount of the tax. The direct effect on consumption and obesity is likely to be smaller than expected in much of the literature that found or assumed full shifting or even overshifting of taxes. In light of the uncertainty about the effectiveness of diet-related fiscal policies, the examination of their cost-effectiveness by only a minority of studies is not surprising, particularly in LMICs. Cecchini and others’ (2010) article was the only published paper to model obesity prevention policies in LMICs, covering Brazil, China, India, Mexico, and South Africa. Their results indicate that fiscal measures (including increasing the price of unhealthy food content or reducing the cost of healthful foods rich in fiber) were less expensive per person than were regulatory or individual interventions; they were the only measures considered that were cost saving for all LMICs at both 20- and 50-year time horizons. In addition, they were cost saving by a magnitude of twice the other interventions considered. Price interventions and regulation appear to produce the largest health gains in the shortest time frame.

As one of the earlier, fairly wide-ranging applications of the modeling approach based on the WHO Choosing Interventions that are Cost-Effective (WHO-CHOICE), Murray and others (2003) modeled salt reduction, mass media health education, and individual treatment, as well as various combinations of different interventions, in two lower-income regions (South-East Asia, with high rates of adult and child mortality, and Latin America, with low adult and child mortality) and one high-income region (Europe, with very low adult and child mortality). Their findings indicate that the nonpersonal interventions have a lower, more favorable cost-effectiveness ratio than do the personalized health service interventions. Voluntary agreements to reduce salt are less cost-effective than legislative measures; salt reduction legislation is estimated to buy one DALY for as little as US$3.74 in South-East Asia and US$2.60 in Latin America. Combinations of salt legislation and mass media programs on healthy behavior have the potential to lower the cost-effectiveness ratio even further. However, the most cost-effective set of interventions is a mix of population-level interventions, preventive interventions, and personalized treatments.

Two follow-up studies to Murray and others (2003) have attempted to provide global or at least multiregional estimates of the cost-effectiveness of salt regulation (as well as other interventions). Asaria and others (2007) modeled the cost and effects of shifts in the distribution of risk factors associated with salt intake and tobacco use on chronic disease mortality for 23 countries that account for 80 percent of chronic disease burden in LMICs. They showed that, over 10 years (2006–15), 13.8 million deaths could have been averted by implementation of these interventions, at a cost of less than US$0.40 per person per year in low-income countries and lower-middle-income countries and US$0.50–US$1.00 per person per year in upper-middle-income countries, as of 2005. Ortegon and others (2012) provide updated evidence on broadly similar interventions in Africa and South-East Asia. In the salt domain, they model the cost-effectiveness of salt reduction in processed foods via voluntary agreements with industry and salt reduction in processed foods via legislation. Rubinstein and others used a more geographically focused application of the WHO-CHOICE approach in two closely related papers, one focusing on Buenos Aires (Rubinstein and others 2009) and the other on Argentina as a whole (Rubinstein and others 2010). The interventions modeled in both studies are similar, including lowering salt intake in the population through voluntary agreements to reduce the levels of salt in bread and providing mass education programs and individual treatment options (Murray and others 2003). The findings in Argentina indicate that any salt reduction would be cost saving; the Buenos Aires–related study suggests that a salt reduction policy would cost very little and would be more cost-effective than a mass media campaign.

Ferrante and others (2012) also looked at salt reduction in Argentina using a simulation model not based on WHO-CHOICE. They analyzed the costs and expected effects of a slightly different salt-related intervention entailing a salt content reduction by 5–25 percent, not only in bread but also in a wider range of food groups that contribute a significant percentage of the salt consumed in the normal diet (for example, bread products, meat products, canned foods, soups, and dressings). Results suggested that this intervention was cost saving and produced substantial benefits to population-wide, diet-related health outcomes. The expectation that salt reduction may be cost saving, applied on its own or in combination with other interventions, has been supported by evidence from four countries in the eastern Mediterranean region (Mason and others 2014). This study evaluated three policies to reduce dietary salt intake, alone and in combination: a health promotion campaign, labeling of food packaging, and mandatory reformulation of salt content in processed food.

In light of the scarcity of evidence of policy effect in high-income countries as well, cost-effectiveness estimates of trans fat policies are difficult to obtain. A recent exception is a much-discussed contested modeling study by Allen and others (2015) that simulated costs and effects of three options for further restricting trans fat consumption in England: a ban of trans fatty acids in processed foods, improved labeling of trans fatty acids, and a restaurant ban of trans fatty acids. The researchers had a specific interest in examining the distributional effects of the various approaches across different socioeconomic groups. The reported findings suggest that the expected health effects of a total ban, as well as policies to improve labeling or simply remove trans fatty acids from restaurants and fast food stores, would lead to a considerable reduction in coronary heart disease mortality. Moreover, these benefits would be larger among lower socioeconomic groups—a rare example of an intervention that may increase average population health and health equity. In addition, the study predicts large cost savings from these policies. However, through inclusion of informal care costs and productivity costs, the cost categories in the analysis of cost-effectiveness reach far beyond the types of costs commonly included in health economic evaluations. Nevertheless, the study is critical of the health and economic effects of a continued reliance on industry to voluntarily reformulate products.

Conclusions

Suboptimal diet is the single-largest risk factor for poor health globally. Specific population interventions, including taxation and subsidies, food regulations, mass media campaigns, and school and workplace interventions, appear effective in improving diet. Many such interventions may be highly cost-effective (efficient health gained per dollar spent) or even cost saving (health gains with reduced overall spending). These interventions are highly attractive and complement the preventive health system strategies promoted in high-, middle-, and low-income countries. Selected policy interventions may also reduce health disparities.

Specific knowledge gaps remain in quantitative effectiveness and cost-effectiveness of several dietary policies in different settings and within different population subgroups. These gaps highlight the urgent need for governments, foundations, advocacy groups, and private industry to prioritize relevant implementation and evaluation of these approaches.

Note

World Bank Income Classifications as of July 2014 are as follows, based on estimates of gross national income (GNI) per capita for 2013:

• Low-income countries (LICs) = US$1,045 or less
• Middle-income countries (MICs) are subdivided:

  1. lower-middle-income = US$1,046 to US$4,125
  2. upper-middle-income (UMICs) = US$4,126 to US$12,745
• High-income countries (HICs) = US$12,746 or more.

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