Antenatal multiple micronutrient supplements versus iron-folic acid supplements and birth outcomes: Analysis by gestational age assessment method.

Meta-analyses consistently have found that antenatal multiple micronutrient supplementation (MMS) compared with iron and folic acid (IFA) alone reduce adverse birth outcomes. In 2020, the World Health Organization (WHO) placed a conditional recommendation for MMS and requested additional trials using ultrasounds to establish gestational age, because the evidence on low birthweight (LBW), preterm birth and small for gestational age (SGA) was considered inconsistent. We conducted meta-analyses to determine if the effects of MMS on LBW, preterm birth and SGA differed by gestational age assessment method. Using data from the 16 trials in the WHO analyses, we calculated the effect estimates of MMS versus IFA on birth outcomes (generic inverse variance method and random effects model) stratified by method of gestational age assessment: ultrasound, prospective collection of the date of last menstrual period (LMP) and confirmation of pregnancy by urine test and recall of LMP. The effects of MMS versus IFA on birthweight, preterm birth and SGA appeared consistent across subgroups with no evidence of subgroup differences (p > 0.05). When limited to the seven trials that used ultrasound, the beneficial effects of MMS were demonstrated: risk ratios of 0.87 (95% confidence interval [CI] 0.78-0.97) for LBW, 0.90 (95% CI, 0.79-1.03) for preterm birth and 0.9 (95% CI, 0.83-0.99) for SGA. Sensitivity analyses indicated consistency in the results. These results, together with recent analyses demonstrating comparable effects of MMS (vs. IFA) on maternal anaemia outcomes, strengthen the evidence to support a transition from IFA to MMS programmes in low- and middle-income countries.

Calcium status assessment at the population level: Candidate approaches and challenges.

Inadequate dietary calcium intake is a global public health problem that disproportionately affects low- and middle-income countries. However, the calcium status of a population is challenging to measure, and there are no standard methods to identify high-risk communities even in settings with an elevated prevalence of a disease caused or exacerbated by low calcium intake (e.g., rickets). The calcium status of a population depends on numerous factors, including intake of calcium-rich foods; the bioavailability of the types of calcium consumed in foods and supplements; and population characteristics, including age, sex, vitamin D status, and genetic attributes that influence calcium retention and absorption. The aim of this narrative review was to assess candidate indicators of population-level calcium status based on a range of biomarkers and measurement methods, including dietary assessment, calcium balance studies, hormonal factors related to calcium, and health outcomes associated with low calcium status. Several promising approaches were identified, but there was insufficient evidence of the suitability of any single indicator to assess population calcium status. Further research is required to develop and validate specific indicators of calcium status that could be derived from the analysis of data or samples that are feasibly collected in population-based surveys.

Economic Evaluation of Individualized Nutritional Support for Hospitalized Patients with Chronic Heart Failure.

Background Malnutrition is a highly prevalent risk factor in hospitalized patients with chronic heart failure (CHF). A recent randomized trial found lower mortality and improved health outcomes when CHF patients with nutritional risk received individualized nutritional treatment. Objective To estimate the cost-effectiveness of individualized nutritional support in hospitalized patients with CHF. Methods This analysis used data from CHF patients at risk of malnutrition (N = 645) who were part of the Effect of Early Nutritional Therapy on Frailty, Functional Outcomes and Recovery of Undernourished Medical Inpatients Trial (EFFORT). Study patients with CHF were randomized into (i) an intervention group (individualized nutritional support to reach energy, protein, and micronutrient goals) or (ii) a control group (receiving standard hospital food). We used a Markov model with daily cycles (over a 6-month interval) to estimate hospital costs and health outcomes in the comparator groups, thus modeling cost-effectiveness ratios of nutritional interventions. Results With nutritional support, the modeled total additional cost over the 6-month interval was 15,159 Swiss Francs (SF). With an additional 5.77 life days, the overall incremental cost-effectiveness ratio for nutritional support vs. no nutritional support was 2625 SF per life day gained. In terms of complications, patients receiving nutritional support had a cost savings of 6214 SF and an additional 4.11 life days without complications, yielding an incremental cost-effectiveness ratio for avoided complications of 1513 SF per life day gained. Conclusions On the basis of a Markov model, this economic analysis found that in-hospital nutritional support for CHF patients increased life expectancy at an acceptable incremental cost-effectiveness ratio.

Prospective validation of five malnutrition screening and assessment instruments among medical inpatients: Secondary analysis of a randomized clinical trial.

BACKGROUND & AIMS: Screening for malnutrition upon hospital admission is the first crucial step for proper nutritional assessment and treatment. While several nutritional screening and assessment instruments exist, there is a lack of head-to-head validation of these instruments. We studied the ability of five different nutrition screening and assessment instruments to predict 1-year mortality and response to nutritional treatment in participants of the EFFORT randomized trial. METHODS: In this secondary analysis of a Swiss-wide multicenter, randomized clinical trial comparing individualized nutritional support with usual care nutrition in medical inpatients, we prospectively classified patients as low, intermediate, and high nutritional risk based on five nutritional screening and assessment instruments (NRS 2002, SGA, SNAQ, MNA and MUST). RESULTS: Overall mortality at 1-year in the 1866 included patients was 30.4%. There were significant correlations and a significant concordance between all instruments with r-values ranging from 0.23 to 0.55 and kappa values ranging from 0.10 to 0.36. While high nutritional risk was associated with higher mortality in all instruments, SGA and MNA showed the strongest association with adjusted odds ratios of 3.17 (95%CI, 2.18 to 4.61, p < 0.001) and 3.45 (95%CI, 2.28 to 5.22, p < 0.001). When comparing mortality in intervention group patients to control group patients stratified by severity of malnutrition, there was overall no clear trend towards more benefit in patients with more severe malnutrition, with NRS 2002 and SGA showing the most pronounced relationship between the severity of malnutrition and reduction in mortality as a response to nutritional support. CONCLUSION: Among all five screening and assessment instruments, higher nutritional risk was associated with higher risk for mortality and adverse clinical outcome, but not with more or less treatment response from nutritional support with differences among scores. Adding more specific parameters to these instruments is important when using them to decide for or against nutritional support interventions in an individual patient. TRIAL REGISTRATION: ClinicalTrials.gov NCT02517476.

Cost savings associated with nutritional support in medical inpatients: an economic model based on data from a systematic review of randomised trials.

BACKGROUND AND AIMS: Nutritional support improves clinical outcomes during hospitalisation as well as after discharge. Recently, a systematic review of 27 randomised, controlled trials showed that nutritional support was associated with lower rates of hospital readmissions and improved survival. In the present economic modelling study, we sought to determine whether in-hospital nutritional support would also return economic benefits. METHODS: The current economic model applied cost estimates to the outcome results from our recent systematic review of hospitalised patients. In the underlying meta-analysis, a total of 27 trials (n=6803 patients) were included. To calculate the economic impact of nutritional support, a Markov model was developed using transitions between relevant health states. Costs were estimated accounting for length of stay in a general hospital ward, hospital-acquired infections, readmissions and nutritional support. Six-month mortality was also considered. The estimated daily per-patient cost for in-hospital nutrition was US$6.23. RESULTS: Overall costs of care within the model timeframe of 6 months averaged US$63 227 per patient in the intervention group versus US$66 045 in the control group, which corresponds to per patient cost savings of US$2818. These cost savings were mainly due to reduced infection rate and shorter lengths of stay. We also calculated the costs to prevent a hospital-acquired infection and a non-elective readmission, that is, US$820 and US$733, respectively. The incremental cost per life-day gained was -US$1149 with 2.53 additional days. The sensitivity analyses for cost per quality-adjusted life day provided support for the original findings. CONCLUSIONS: For medical inpatients who are malnourished or at nutritional risk, our findings showed that in-hospital nutritional support is a cost-effective way to reduce risk for readmissions, lower the frequency of hospital-associated infections, and improve survival rates.

Economic evaluation of individualized nutritional support in medical inpatients: Secondary analysis of the EFFORT trial.

BACKGROUND & AIMS: Existing guidelines support the importance of nutritional interventions for medical inpatients at malnutrition risk to alleviate the impact of malnutrition on outcomes. While recent studies have reported positive effects of nutritional support on health outcomes, limited evidence exists on whether in-hospital nutritional support also results in economic advantages. We report the results of the economic evaluation of EFFORT-a pragmatic, investigator-initiated, open-label, multicenter trial. METHODS: A total of 2028 medical inpatients at nutritional risk were randomly assigned to receive individualized nutritional support to reach protein and energy goals (intervention group; n = 1015) or standard hospital food (control group; n = 1013). To calculate the economic impact of nutritional support, a Markov model was developed with relevant health states. Costs were estimated for days in normal hospital ward and in the Intensive Care Unit (ICU), hospital-acquired complications, and nutritional support. We used a Euro conversion rate of 0.93216 Euro for 1 Swiss Franc (CHF). RESULTS: The estimated per-patient cost was CHF90 (83.78 €) for the in-hospital nutritional support and CHF283.85 (264.23 €) when also considering dietitian consultation time. Overall costs of care within 30 days of admission averaged CHF29,263 (27,240 €) per-patient in the intervention group versus CHF29,477 (27,439 €) in the control group resulting in per-patient cost savings of CHF214 (199 €). Per-patient cost savings was CHF19.56 (18.21 €) when also accounting for dietician costs (full cost analysis). These cost savings were mainly due to reduced ICU length of stay and fewer complications. We also calculated costs to prevent adverse outcomes, which were CHF276 (256 €) for one severe complication, CHF2,675 (2490 €) for one day in ICU, and CHF7,975 (7423 €) for one death. For the full cost analysis, these numbers were CHF872 (811 €), CHF8,459 (7874 €) and CHF25,219 (23,475 €). Sensitivity analyses confirmed the original findings. CONCLUSIONS: Our evaluation demonstrates that in-hospital nutritional support for medical inpatients is a highly cost-effective intervention to reduce risks for ICU admissions and hospital-associated complications, while improving patient survival. The positive clinical and economic benefits of nutritional support in at-risk medical inpatients calls for comprehensive nutrition programs, including malnutrition screening, consultation, and nutritional support. TRIAL REGISTRATION: ClinicalTrials.gov number, NCT02517476.

Setting research priorities on multiple micronutrient supplementation in pregnancy.

Prenatal micronutrient deficiencies are associated with negative maternal and birth outcomes. Multiple micronutrient supplementation (MMS) during pregnancy is a cost-effective intervention to reduce these adverse outcomes. However, important knowledge gaps remain in the implementation of MMS interventions. The Child Health and Nutrition Research Initiative (CHNRI) methodology was applied to inform the direction of research and investments needed to support the implementation of MMS interventions for pregnant women in low- and middle-income countries (LMIC). Following CHNRI methodology guidelines, a group of international experts in nutrition and maternal health provided and ranked the research questions that most urgently need to be resolved for prenatal MMS interventions to be successfully implemented. Seventy-three research questions were received, analyzed, and reorganized, resulting in 35 consolidated research questions. These were scored against four criteria, yielding a priority ranking where the top 10 research options focused on strategies to increase antenatal care attendance and MMS adherence, methods needed to identify populations more likely to benefit from MMS interventions and some discovery issues (e.g., potential benefit of extending MMS through lactation). This exercise prioritized 35 discrete research questions that merit serious consideration for the potential of MMS during pregnancy to be optimized in LMIC.

Nutritional Risk Screening and Assessment.

Malnutrition is an independent risk factor that negatively influences patients' clinical outcomes, quality of life, body function, and autonomy. Early identification of patients at risk of malnutrition or who are malnourished is crucial in order to start a timely and adequate nutritional support. Nutritional risk screening, a simple and rapid first-line tool to detect patients at risk of malnutrition, should be performed systematically in patients at hospital admission. Patients with nutritional risk should subsequently undergo a more detailed nutritional assessment to identify and quantify specific nutritional problems. Such an assessment includes subjective and objective parameters such as medical history, current and past dietary intake (including energy and protein balance), physical examination and anthropometric measurements, functional and mental assessment, quality of life, medications, and laboratory values. Nutritional care plans should be developed in a multidisciplinary approach, and implemented to maintain and improve patients' nutritional condition. Standardized nutritional management including systematic risk screening and assessment may also contribute to reduced healthcare costs. Adequate and timely implementation of nutritional support has been linked with favorable outcomes such as a decrease in length of hospital stay, reduced mortality, and reductions in the rate of severe complications, as well as improvements in quality of life and functional status. The aim of this review article is to provide a comprehensive overview of nutritional screening and assessment methods that can contribute to an effective and well-structured nutritional management (process cascade) of hospitalized patients.

Hidden Hunger: Solutions for America's Aging Populations.

The global population, including the United States, is experiencing a demographic shift with the proportion of older adults (aged ≥ 65 years) growing faster than any other age group. This demographic group is at higher risk for developing nutrition-related chronic conditions such as heart disease and diabetes as well as infections such as influenza and pneumonia. As a result, an emphasis on nutrition is instrumental for disease risk reduction. Unfortunately, inadequate nutrient status or deficiency, often termed hidden hunger, disproportionately affects older adults because of systematic healthcare, environmental, and biological challenges. This report summarizes the unique nutrition challenges facing the aging population and identifies strategies, interventions, and policies to address hidden hunger among the older adults, discussed at the scientific symposium "Hidden Hunger: Solutions for America's Aging Population", on March 23, 2018.

Risk of Malnutrition Is an Independent Predictor of Mortality, Length of Hospital Stay, and Hospitalization Costs in Stroke Patients.

BACKGROUND: Malnutrition is associated with poor outcomes after stroke. Nutrition screening tools (NSTs) are used to identify patients at risk of malnutrition, but so far no NST has been validated for use with patients who have had a stroke. This study aimed to determine the ability of the Malnutrition Universal Screening Tool (MUST) to predict poor outcomes in stroke patients, including mortality, cumulative length of hospital stay (LOS), and hospitalization costs. METHODS: Patients were recruited from consecutive admissions at 2 hyperacute stroke units in London and were screened for risk of malnutrition (low, medium, and high) according to MUST. Six-month outcomes were obtained for each patient through a national database. RESULTS: Of 543 recruited patients, 51% were males, the mean age was 75 years, and 87% had an ischemic stroke. Results showed a highly significant increase in mortality with increasing risk of malnutrition (P < .001). This association remained significant after adjusting for age, severity of stroke, and a range of stroke risk factors (P < .001). For those patients who survived, the LOS and hospitalization costs increased with increasing risk of malnutrition (P < .001 and P = .049, respectively). This association remained significant in the adjusted model (P < .001 and P = .001, respectively). CONCLUSIONS: Risk of malnutrition is an independent predictor of mortality, LOS, and hospitalization costs at 6 months post stroke. Research is needed to determine if nutritional support for medium- or high-risk patients results in better outcomes. Routine screening of stroke patients for risk of malnutrition is recommended.