Diet Quality Is Associated With Mortality in Adults Aged 80 Years and Older: A Prospective Study

Abstract

OBJECTIVES Diet quality has been associated with health outcomes and quality of life. However, the association between diet quality and mortality in older people, those aged 80 years and older, is understudied. Therefore, we conducted a prospective study to examine whether better diet quality, assessed by a validated dietary screening tool (DST), was associated with lower mortality in those aged 80 years and older. METHODS Our study included 1990 participants (812 men and 1178 women), with a mean age of 84.1 years at baseline (ranging from 80 to 102 years old), from the Geisinger Rural Aging Study longitudinal cohort in Pennsylvania. Baseline descriptive information was obtained in 2009, and the DST was administered via mailed survey. The DST is composed of 25 food‐ and behavior‐specific questions associated with dietary intake that generate a diet quality score ranging from 0 (lowest) to 100 (highest). Death was identified using electronic medical record and the Social Security Death Index data. Hazard ratios (HRs) and 95% confidence intervals (CIs) across three diet quality categories were calculated by using Cox proportional hazards models after adjusting for potential confounders. RESULTS Over 8 years of follow‐up (October 2009‐February 2018), 931 deaths were documented. Higher diet quality was associated with lower mortality risk (P‐trend = .04). Participants with high diet quality (defined as DST scores >75) had significantly lower risk of mortality compared with those with low diet quality (defined as DST scores <60) after adjusting for potential risk factors (adjusted HR = 0.76; 95% CI = 0.59‐0.97). CONCLUSION Diet quality, assessed by DST, is significantly associated with risk of mortality in older adults aged 80 years and older in our prospective cohort. Our results indicate that nutrition may have an important role in healthy aging, and more studies are needed to develop appropriate dietary recommendations for older persons. J Am Geriatr Soc 67:2180–2185, 2019

Healthy Dietary Intake Behavior Potentially Modifies the Negative Effect of COVID-19 Lockdown on Depression: A Hospital and Health Center Survey

“…Social and environmental factors were found as determinants of eating behavior in a previous study (56). Therefore, nutrition support programs are important for vulnerable people to improve their dietary intake behavior (57,58), especially during the pandemic and home confinement (30,31). Our study shows that people who were under the lockdown period had a higher likelihood of depression.…”

Evaluation of Dietary Patterns and All-Cause Mortality

“…After dual screening, 11 547 relevant studies were identified. The body of evidence included 153 articles (involving 6 550 664 individuals), of which 1 was from a randomized clinical trial (RCT) 18 and 152 were from observational studies 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 ,…”

“…Studies enrolled adults and older adults (aged 17-84 years at baseline) from 28 countries with a high or very high Human Development Index 16 classification (Australia, Belgium, Canada, Czech Republic, Croatia, Denmark, Finland, France, Germany, Greece, Hong Kong, Hungary, Iran, Italy, Japan, Korea, Norway, Netherlands, Poland, Portugal, Russia, Serbia, Singapore, Spain, Sweden, Switzerland, United Kingdom, and United States). Fifty-three studies 21 , 23 , 24 , 27 , 29 , 32 , 33 , 37 , 39 , 40 , 42 , 43 , 44 , 46 , 47 , 52 , 56 , 57 , 58 , 59 , 60 , 61 , 72 , 73 , 74 , 78 , 83 , 86 , 94 , 95 , 96 , 98 , 100 , 101 , 102 , 104 , 107 , 110 , 118 , 125 , 126 , 127 , 129 , 135 , 137 , 150 , 158 , 160 , 161 , 163 , 166 originated from the US. Some studies exclusively enrolled female 29 , …”

“…The approaches for assessing dietary patterns included an RCT 18 ; a priori methods, such as index or score analysis 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 ,…”

“…Many of the indices considered alcoholic beverage intake in low to moderate amounts or within a threshold (eg, 10-25 g/d; 0.5-1.5 drinks/d for women and 0.5-2.0 drinks/d for men) as a positive The associations reported between a priori-derived dietary patterns and ACM remained in sensitivity or subgroup analyses after combining the dietary patterns with anthropometry, physical activity, and/or smoking status 24,35,37,44,53,118 ; performing stratification or additional adjustment for anthropometry, sex, age, educational level, race/ethnicity, and/or smoking status 25,34,37,46,47,52,76,83,[85][86][87]95,96,98,99,104,111,113,115,119,125,126 ; excluding early deaths or the first few years of follow-up results 25,35,49,57,58,63,65,72,76,82,96,99,[111][112][113]119,125,128 ; accounting for chronic disease status (eg, diabetes or CVD…”