| Literature DB >> 29634725 |
Jonathan Pearson-Stuttard1,2, Chris Kypridemos1, Brendan Collins1, Dariush Mozaffarian3, Yue Huang3, Piotr Bandosz1,4, Simon Capewell1, Laurie Whitsel5, Parke Wilde3, Martin O'Flaherty1, Renata Micha3.
Abstract
BACKGROUND: Sodium consumption is a modifiable risk factor for higher blood pressure (BP) and cardiovascular disease (CVD). The US Food and Drug Administration (FDA) has proposed voluntary sodium reduction goals targeting processed and commercially prepared foods. We aimed to quantify the potential health and economic impact of this policy. METHODS ANDEntities:
Mesh:
Substances:
Year: 2018 PMID: 29634725 PMCID: PMC5892867 DOI: 10.1371/journal.pmed.1002551
Source DB: PubMed Journal: PLoS Med ISSN: 1549-1277 Impact factor: 11.069
Fig 1Simplified model structure.
CHD, coronary heart disease; NHANES, National Health and Nutrition Examination Survey; QALY, quality-adjusted life year.
The US IMPACT Food Policy Model data sources.
| Parameter | Outcome | Details | Comments | Source |
|---|---|---|---|---|
| Population size estimates | Population | July 1 US resident population from the Vintage 2014 postcensal series, the revised 2000–2009 intercensal series, and the 1990–1999 intercensal series | Stratified by year, age, sex, bridged race, and Hispanic origin | CDC WONDER bridged-race population estimates 1990–2014 [ |
| Population projections | Population | 2014–2060 US population projections produced by the Census Bureau in 2014 | Stratified by year, age, sex, race, and ethnicity | US Census Bureau via CDC WONDER national population projections 2014–2060 [ |
| Mortality | Deaths from CHD, stroke, and any other non-modeled causes | Underlying cause of death 1999–2015 | Stratified by year, age, sex, race, ethnicity, and cause of death | US Department of Health and Human Services and CDC NCHS via CDC WONDER underlying cause of death 1999–2015 [ |
| Sodium exposure | Exposure of individuals | NHANES | Anonymized, individual-level datasets; years 2009–2014 | CDC NCHS NHANES data [ |
| Systolic blood pressure exposure | Exposure of individuals | NHANES | Anonymized, individual-level datasets; years 1999–2014 | CDC NCHS NHANES data [ |
| Effect of sodium consumption on systolic blood pressure | Systolic blood pressure change | Meta-analysis/meta-regression of 103 trials | Only trials with duration >7 days were analyzed | Text S1 in Mozaffarian et al. [ |
| Reference level of sodium consumption | Ideal sodium consumption below which no risk was considered to occur | Evidence from ecological studies, randomized trials, and meta-analyses of prospective cohort studies | Intake levels associated with the lowest risk ranged from 614 to 2,391 mg/day; in large, well-controlled randomized feeding trials, the lowest tested intake for which blood pressure reductions were clearly documented was 1,500 mg/day | Text S4 and Table S3 in Mozaffarian et al. [ |
| Relative risk for systolic blood pressure | CHD and stroke incidence (ICD-10: I20–I25 and I60–I69) | Pooled analysis of 2 individual-level meta-analyses | Stratified by age and sex; adjusted for regression dilution and total blood cholesterol and, where available, lipid fractions (HDL and non-HDL cholesterol), diabetes, weight, alcohol consumption, and smoking at baseline | eTable 5 in Micha et al. [ |
| Mortality from any cause excluding CHD and stroke | Individual-level meta-analysis of 48 prospective cohort studies | Adjusted for age, sex, race or ethnicity, deprivation, smoking, diabetes, inactivity, alcohol, and obesity | Figure 4 in Stringhini et al. [ | |
| Reference level of systolic blood pressure | Ideal systolic blood pressure below which no risk was considered to occur | Evidence from randomized trials of antihypertensive drugs and the INTERSALT study | There may be health benefits by lowering systolic blood pressure down to 110 mm Hg | Singh et al. [ |
| Health state utility values | For CHD, stroke, hypertension, and their combinations | Uses EQ-5D-3L data from MEPS 2000–2002 | We used the published regression coefficients to estimate utility values by age, sex, race, ethnicity, income, education, and number of chronic conditions | Tables 2 and 3 in Sullivan et al. [ |
| Disease costs | Medical, mortality, and morbidity costs for CHD, stroke, and hypertension | Based on MEPS | Stratified by age, sex, and race; adjusted for comorbidities | Khavjou et al. [ |
| Informal care costs for stroke | Difference-in-differences technique in propensity-score-matched populations | Table 3 in Joo et al. [ | ||
| Informal care costs for CHD | Costs were extrapolated for US settings | Table 5 in Leal et al. [ | ||
| Government costs to administer the policy | Administration costs for new restaurant menu and vending machine labeling regulation, including cost for outreach, education, review of regulatory issues, developing training for inspectors, and related functions | US Food and Drug Administration [ | ||
| Government costs to monitor and evaluate the policy | UK Food Standards Agency impact assessment of UK salt reduction strategy | We assumed sodium reformulation to have same administrative costs | Collins et al. [ | |
| Industry costs to reformulate products | Spreadsheet model | The model accounted for variations in product formula complexity, company size, reformulation type, compliance period, and other factors | Muth et al. [ |
CDC, US Centers for Disease Control and Prevention; CHD, coronary heart disease; HDL, high-density lipoprotein; MEPS, Medical Expenditure Panel Survey; NCHS, National Center for Health Statistics; NHANES, National Health and Nutrition Examination Survey.
Health-related model estimates over the 20-year simulation period from 2017 to 2036, for US adults aged 30 to 84 years.
| Outcome | Optimal policy scenario | Modest policy scenario | Pessimistic policy scenario |
|---|---|---|---|
| Median sodium consumption in 2036 (mg/day) | 2,224 | 2,524 | 2,789 |
| Median SBP in 2036 (mm Hg) | 114.0 | 114.5 | 115.0 |
| CHD cases prevented or postponed | 260,000 | 120,000 | 63,000 |
| Stroke cases prevented or postponed | 180,000 | 93,000 | 52,000 |
| CHD deaths prevented or postponed | 22,000 | 11,000 | 7,400 |
| Stroke deaths prevented or postponed | 13,000 | 7,400 | 5,600 |
| Non-CVD deaths prevented or postponed | 48,000 | 24,000 | 7,400 |
| All deaths prevented or postponed | 83,000 | 41,000 | 22,000 |
| Life years gained | 530,000 | 260,000 | 180,000 |
| Discounted QALYs gained(millions) | 2.1 m | 1.1 m | 0.69 m |
Values are the median estimate (95% uncertainty interval). Results are rounded to first decimal for SBP, fourth significant digit for sodium consumption, and second significant digit for other outcomes.
*Negative numbers of deaths prevented or postponed for specific causes of death are a direct consequence of the mortality competing risk framework we implemented in the model. They represent synthetic individuals for whom the prevention of their death from a specific disease (i.e., CHD) due to the policy led to their death from another competing cause (i.e., non-CVD) in the same year.
CHD, coronary heart disease; CVD, cardiovascular disease; m, million; QALY, quality-adjusted life year; SBP, systolic blood pressure.
Fig 2Median US sodium consumption among adults aged 30–84 years under the baseline projection and 3 modeled scenarios.
The dashed horizontal line depicts the 2015–2020 Dietary Guidelines for Americans recommended upper bound of 2,300 mg/day [5].
QALYs gained and costs per 100,000 person-years.
| Outcome | Optimal scenario | Modest scenario | Pessimistic scenario |
|---|---|---|---|
| 61 (50 to 71) | 33 (27 to 40) | 19 (14 to 24) | |
| −550,000 | −240,000 | −120,000 | |
| −1,400,000 | −680,000 | −410,000 |
Costs are in 2017 US dollars. Negative costs represent savings. Readers can calculate similar estimates for other outputs by dividing by 4.7 billion (the number of person-years over the 20-year simulated period).
QALY, quality-adjusted life year.
Impact inventory and cost-effectiveness analysis of model outputs for individuals aged 30 to 84 years, assessed cumulatively over the 20-year simulation period from 2017 to 2036.
| Output | Optimal policy scenario | Modest policy scenario | Pessimistic policy scenario |
|---|---|---|---|
| −57 bn | −30 bn | −19 bn | |
| Hypertension medical costs | −18 bn | −9.3 bn | −4.4 bn |
| Hypertension productivity costs | −12 bn | −6.4 bn | −3.5 bn |
| CHD medical costs | −7.1 bn | −3.3 bn | −2.8 bn |
| CHD mortality productivity costs | −4.8 bn | −2.3 bn | −1.8 bn |
| CHD morbidity productivity costs | −1.3 bn | −0.64 bn | −0.5 bn |
| CHD informal care costs | −1.5 bn | −0.69 bn | −0.58 bn |
| Stroke medical costs | −5.4 bn | −2.9 bn | −2.4 bn |
| Stroke mortality productivity costs | −2.3 bn | −1.3 bn | −1.0 bn |
| Stroke morbidity productivity costs | −0.76 bn | −0.41 bn | −0.33 bn |
| Stroke informal care costs | −3.1 bn | −1.5 bn | −1.2 bn |
| 17 bn | 10 bn | 7.3 bn | |
| Policy administration costs | 0.16 bn | 0.16 bn | 0.16 bn |
| Policy monitoring costs | 0.029 bn | 0.029 bn | 0.029 bn |
| Policy industry costs | 16 bn | 10 bn | 7.2 bn |
| −31 bn | −16 bn | −9.7 bn | |
| −41 bn | −19 bn | −12 bn | |
| 250 bn | 130 bn | 81 bn | |
| Dominant (dominant to dominant) | Dominant (dominant to dominant) | Dominant (dominant to 540) |
Results are rounded to the second significant digit. Costs are median of each distribution so may not add up to totals. Negative costs represent savings. Costs are presented in billions of discounted 2017 US dollars. Dominant = less costly and more effective than the alternative.
bn, billion; CHD, coronary heart disease; QALY, quality-adjusted life year.
Fig 3Estimated disaggregated discounted cumulative costs for the simulated period 2017 to 2036.
Negative costs represent savings. The shaded areas depict 95% uncertainty intervals. USD, US dollars.
Fig 4Cost-effectiveness plane by the end of simulation (year 2036).
Each colored dot is the result of a stochastic Monte Carlo iteration. The black dots are the median combinations of cumulative discounted net costs (2017 US dollars) and discounted net QALYs for each simulated scenario, and the ellipses depict the 95% uncertainty interval. Negative costs represent savings. QALY, quality-adjusted life year; USD, US dollars.
Fig 5Estimated probability of cost-effective and cost-saving policy over the 20-year simulated period.
Cost-effectiveness at the willingness to pay value of $100,000 per quality-adjusted life year.