Physical activity and mortality in frail elderly

Structured
Literature
Review
Physical activity and all-cause mortality
amongst frail elderly members of society
29/03/2017; edited 25/09/2017
Module code: EH4010
Module title: Final Year Project
Name: Mark R O’Donovan
Student number: Removed
Project Supervisor: Removed
Date of Submission: 29/03/17

i
Student declaration form
Removed from this version
Please Note
- Some parts of this easy have been removed and this
is on the basis of personal information, content
belonging to others, or repetition of content.
- This essay is purely academic and I will not accept
legal responsibility for any information,
interpretations or options contained herein.
- Feel free to utilise, critique, print or reference any of
this content 

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Acknowledgments
Firstly I would like to extend a warm thank you to my supervisor and lecturer Removed
for his feedback and guidance relating to this review. He not only helped steer the review
in the right direction but also answered many relevant burning questions I had throughout
the year.
Additionally of particular value to this review were previous Public Health research
projects and the feedback relating to these, provided by Removed and Removed. Also
the contribution of Removed who introduced me to the field of epidemiology and greatly
enhanced my understanding of this area.
My third year work placement at the World Health Organization Regional Office for
Europe also provided me with skills and experience that greatly benefited this project and
I would like to particularly thank Removed, Removed, Removed, Removed, Removed,
and Removed.
I would also like to acknowledge everyone from UCC’s Department of Epidemiology
and Public Health as well as lectures I have had from other departments, that have all
not only contributed to this work but have enhanced my university experience, skills, and
critical thinking. In particular I would like to mention the academic contributions of
Removed, Removed, Removed, Removed, Removed, Removed, Removed, Removed
and the head of our department Removed.
Last but not least I would like to thank all my friends and family who engaged with this
project and offered me some great tips and advice, it is really appreciated!
Mark R O’Donovan

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Table of contents
Student declaration form [Removed from this version] ................................................................................ i
Acknowledgments ...................................................................................................................................... ii
Table of contents ....................................................................................................................................... iii
List of Tables and Figures .......................................................................................................................... v
Abstract .......................................................................................................................................................... 1
1. Background ................................................................................................................................................ 2
2. Methods...................................................................................................................................................... 5
2.1 Selection/eligibility criteria .................................................................................................................. 5
2.2 Search strategy and results ................................................................................................................... 5
2.2.1 Key words ..................................................................................................................................... 5
2.2.2 Database search strategies........................................................................................................... 6
2.2.3 Database search results................................................................................................................ 6
2.3 Assessment of methodological quality of included studies .................................................................. 7
3. Results ........................................................................................................................................................ 8
3.1 Number and type of studies included in the review.............................................................................. 8
3.2 Design and summary of the methodological quality of included studies ............................................. 8
Study 1: Landi et al. (2004)........................................................................................................................ 8
3.2 1a Aim and study setting ................................................................................................................. 8
3.2 1b Cohort selection and cohort characteristics ............................................................................... 8
3.2 1c Measurement of exposure.......................................................................................................... 9
3.2 1d Measurement of outcome.......................................................................................................... 9
3.2 1e Follow-up of cohort, data analysis and controlling for confounding.......................................... 9
3.2 1f Summary of the quality of the cohort study by Landi et al. 2004 ............................................. 10
3.2.1g Overall assessment of the risk of bias....................................................................................... 11
Study 2: Brown et al. (2016) .....................................................................................................................11
3.2 2a Aim and study setting ............................................................................................................... 11
3.2 2b Cohort selection and cohort characteristics ............................................................................. 11
3.2 2c Measurement of exposure........................................................................................................ 12
3.2 2d Measurement of outcome........................................................................................................ 13
3.2 2e Follow-up of cohort, data analysis and controlling for confounding........................................ 13
3.2 1f Summary of the quality of the cohort study by Brown et al. 2016 ........................................... 14
3.2.1g Overall assessment of the risk of bias....................................................................................... 14

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3.3 Results: Associations between physical activity, dietary influence, and mortality in frail elderly......16
Results Tables............................................................................................................................................18
Landi et al. (2004) ................................................................................................................................ 18
Brown et al. (2016) .............................................................................................................................. 19
Discussion .....................................................................................................................................................21
Limitations of this structured literature review..........................................................................................23
Conclusions ...................................................................................................................................................25
Implications for practice............................................................................................................................25
Recommendations for future research.......................................................................................................25
References .....................................................................................................................................................26
Appendices [Removed from this version]...................................................................................................30
Appendix A: Reasons for exclusion of read studies (N=30) .....................................................................30
Appendix B: Critical Appraisals ...............................................................................................................30
Appendix C: Full copies of papers by Landi et al. (2004) and Brown et al. (2016) ..................................30

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List of Tables and Figures
Page
Tables
Table 2.1: Selection/Eligibility Criteria............................................................................ 5
Table 2.2: Key words........................................................................................................ 5
Table 2.3: Google Scholar search details.......................................................................... 6
Table 2.4: PubMed search details..................................................................................... 6
Table 3.1: Summary of study quality: Landi et al. (2004) – cohort study...................... 10
Table 3.2: Summary of study quality: Brown et al. (2016) – cohort study.................... 14
Table 3.3: Results of cohort studies by Landi et al. (2004) and Brown et al. (2016)..... 16
Table 3.4: Results Table for study 1: Landi et al. (2004)............................................... 18
Table 3.5: Results Table for study 2: Brown et al. (2016) ........................................19-20
Figures
Figure 1.1: Population aged ≥ 60 years and aged ≥ 80 years, by region, 1980-2050....... 2
Figure 1.2: Global age distribution of YLD’s per 100,000 people................................... 3
Figure 2.1: PRISMA 2009 Flow Diagram........................................................................ 7

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Abstract
Background: There is a large volume of existing evidence showing that physical activity
is a protective factor against all causes of mortality in both young and older adults.
However all activity carries a risk of falls and injury and this risk is especially high
amongst vulnerable population sub-groups such as frail elderly individuals. It is
commonly assumed that these high risk groups still receive an overall benefit from being
more physically active.
Objectives: To determine if physical activity is protective against all-cause mortality in
frail elderly members of the community by systematically reviewing the best available
epidemiological evidence.
Methods:
Selection criteria: Systematic reviews, randomised control trials (RCTs), and cohort
studies published in English and examining the relationship between physical activity and
mortality in frail elderly members of the community are considered for inclusion in this
review.
Search Strategy: Google Scholar and PubMed databases were searched for relevant
studies on 17th January 2017.
Quality Assessment: The quality of studies included in this review was assessed using
online appraisal checklists developed by the Critical Appraisal Skills Programme,
Oxford, UK.
Results: 2 cohort studies met the eligibility criteria for inclusion. Samples consisted of
2757 frail elderly community-dwelling persons in Italy, and 1487 prefrail and frail
persons in the USA. All participants were 65 years or older, frail, and followed-up for 1
year or up to 22 years, respectively. There were a number of inconsistent statements and
various sources of recall and measurement bias in both studies; overall the Italian one
was judged to have a low/moderate level of bias and the American one a high level of
bias.
The results of these two studies were consistent with one another and related research.
Adjusting for all know confounders frail elderly people with 2 hours of moderate
physical activity per week had a risk of mortality 49% lower than those with less than
two hours [RR 0.51 (95% CI 0.35–0.73)] and both inactive and active prefrail/frail
elderly had a significantly reduced risk of mortality compared to those who were
sedentary [HR 0.76 (95% CI 0.58–0.98), HR 0.66 (95% CI 0.51–0.86) respectively)].
Diet appears to modify this relationship with prefrail/frail elderly who are both active and
have a good diet receiving the greatest benefit [HR 0.50 (0.29–0.87)].
Conclusions: Due to bias and methodological limitations these findings should be
interpreted cautiously, but they do suggest that the benefits of physical activity can
indeed extend to those suffering from frailty symptoms. This would be the suspected and
desirable result but a good quality randomised controlled trial (RCT) is needed to verify
these findings. Further research is needed into the influence of diet on this relationship.

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1. Background
According to the United Nation’s (2015, p.1) “The world’s population is ageing: virtually
every country in the world is experiencing growth in the number and proportion of older
persons in their population.” As illustrated in Figure 1.1, from their report, the number of
people in the world over the age of 60 are expected to rise from 901 million in 2015 to
1.4 billion by 2030 and 2.1 billion by 2050; and those over 80 years are expected to rise
from 125 million in 2015 to 202 million by 2030 and 434 million by 2050.
Figure 1.1: Population aged ≥ 60 years and aged ≥ 80 years, by region, 1980-2050
(United Nations 2015, p.13)
But living longer does not necessarily mean living in good health and whether living into
older age will increase or decrease disability amongst the elderly population is under
heavy debate with conflicting findings (WHO 2011). The latest data from the Global
Burden of Disease project does show a steady increase in the years of life lost due to
disability (YLD) as people age but is capped at 80 years (see Figure 1.2) and the WHO
have stated in a recent news release that “nearly a quarter (23%) of the overall global

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burden of death and illness is in people aged over 60” due to long term non-
communicable diseases such as cancer, chronic respiratory diseases, heart disease,
musculoskeletal diseases, and mental and neurological disorders (WHO 2014). From
these trends it is clear that keeping our growing elderly population as healthy as possible
is going to be a major focus and challenge for public health in the foreseeable future.
Figure 1.2: Global age distribution of YLD’s per 100,000 people (IHME 2017)
Age in years
One way of tackling this is through a continuation or adoption of healthy lifestyle
behaviours which have been shown not only to increase the length of life at all ages
(Rizzuto et al. 2012, Rizzuto and Fratiglioni 2014) but also to delay and reduce the risk
of illness in old age (Fries 2000, De Groot et al. 2004). From the above it was also noted
that a synergistic relationship existed between multiple healthy lifestyle factors. However
sedentary behaviour alone has recently been shown to be an important risk factor for
mortality in older adults (de Rezende et al. 2014) and the risk factors of inactivity and
prolonged sitting are involved in the combinations of factors that carry the highest risk of
mortality (Ding et al. 2015).

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Physical activity has recently been shown to negate much of the negative effects of
prolonged sitting and sedentary behaviour (Ekelund et al. 2016), and there is growing
evidence showing that physical fitness is more important than risks such as high body
weight (Barry et al. 2014, Yerrakalva et al. 2015). The positive effects of physical
activity on mortality and morbidity are consistently documented throughout the literature
(Warburton et al. 2006, Samitz et al. 2011) and existing randomised control trial
evidence suggests exercise interventions are as effective as many drug interventions in
terms of mortality benefits (Naci and Ioannidis 2013). The benefits of physical activity
also apply to older individuals aged 60 years and over (Hupin et al. 2015), and there is
some evidence that suggests participation in physical activity becomes more protective
against mortality at older ages (Gulsvik et al. 2012).
There are many biological pathways by which exercise can improve body composition,
structure and performance (Mazzeo et al. 1998, Fries 2000, Warburton et al. 2006).
However elderly individuals who suffer from frailty symptoms find it increasingly
difficult to be physically active and are at an increased risk of falls and injury. Speechley
and Tinetti (1991) found that for an elderly community sample those considered frail had
a much higher incidence of falls (52%) compared to those who were categorised as
vigorous (17%), however only 6% of falls for the frail individuals resulted in serious
injury, whereas 22% resulted in serious injury for more vigorous individuals. In light of
these observations and a general lack of evidence it is unclear if the many benefits of
increasing physical activity still outweigh the risks in already frail elderly individuals.

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2. Methods
2.1 Selection/eligibility criteria
The criteria used to select studies relevant for inclusion in this review are outlined below
in Table 2.1.
Table 2.1: Selection/Eligibility Criteria
Types of
studies
Systematic reviews, randomised control trials and cohort studies published
in the English language.
Types of
participants
Studies involving frail elderly people (both sexes, aged ≥65 years).
Types of
exposure
Studies examining the effects of physical activity.
Types of
outcomes
Studies reporting the outcome of mortality (all causes).
2.2 Search strategy and results
Google Scholar and PubMed databases were searched on the 17th
January 2017.
2.2.1 Key words
Search terms to describe the participants, the exposure, and the outcome were
conceptualised following a general search of the literature area, and consultation of
PubMed’s MeSH terms (see Table 2.2).
Table 2.2: Key words
Participants Exposure Outcome
Frail
Frailty
Frailness
Elderly
Older
Old
Physical activity
Physically active
Exercise
Exertion
Mortality
Death
Length of life
Long life
Life expectancy

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2.2.2 Database search strategies
Google Scholar search procedure is summarised in Table 2.3 and PubMed search
procedure is summarised in Table 2.4.
Table 2.3: Google Scholar search details
Database Date searched Search term used1
Limits Search hits
Google
Scholar
17/01/17 (frail OR frailty OR frailness) (elderly
OR older OR old) (intitle:"physical
activity" OR intitle:"physically active”
OR intitle:exercise OR intitle:exertion)
(intitle:mortality OR intitle:death OR
intitle:“length of life” OR intitle:“long
life” OR intitle:“life expectancy”)
English
language
only
54 (including 2
duplicates)
1. Decided to conduct the search with the key words for the exposure and outcome in the title, and the
population key words anywhere in the text. This allows for studies where subgroups such as frail elderly
individuals have been examined but this group was not the main focus of the study i.e. not in title.
Table 2.4: PubMed search details
Database Date searched Search term used1
Limits2
Search hits
PubMed 17/01/17 ((((frail OR frailty OR frailness)) AND
(elderly OR older OR old)) AND
("physical activity"[Title] OR
"physically active"[Title] OR
exercise[Title] OR exertion[Title])) AND
(mortality[Title] OR death[Title] OR
"length of life"[Title] OR "long
life"[Title] OR "life expectancy"[Title])
English
language
only
4 (all of these
were also
located in the
Google Scholar
search)
1. Search term was constructed as follows using PubMed’s advanced search setting:
All field: frail OR frailty OR frailness
All field: elderly OR older OR old
In title: "physical activity" OR "physically active" OR exercise OR exertion
In title: mortality OR death OR "length of life" OR "long life" OR "life expectancy"
2. Did not use other relevant limits such as species, age, or study types, since the number of search hits was
so small and including these extra limits may (did) incorrectly remove poorly indexed but relevant studies.
2.2.3 Database search results
All search hits from the 2 searches detailed above were imported into the EndNote Web®
reference management software and their eligibility based on this review’s criteria (Table
2.1) was determined (see Figure 2.1). With all duplicates removed there was a total of 52
studies; 20 were removed based on title screening, and 30 on assessment of the abstract
or full paper (mainly due to absence of frailty, for full list of reasons see Appendix A),
leaving a total of 2 eligible studies: Landi et al. (2004) and Brown et al. (2016).

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ScreeningIdentification
Figure 2.1: PRISMA 2009 Flow Diagram
2.3 Assessment of methodological quality of included studies
The quality of the two cohort studies included in this review was assessed using the latest
Critical Appraisal Skills Programme (CASP) checklist for cohort studies (CASP 2013).
These completed critical appraisal checklists are included in Appendix B. Based on the
results of these a judgment was made regarding the risk of bias in each study.
Google Scholar
Searched on 17/01/17
(n = 54)
IncludedEligibility
PubMed
Searched on 17/01/17
(n = 4)
Records after duplicates removed
(n = 52)
(Removed: 2GS, 4PM)
Records screened
(n = 52)
Records excluded
(n = 20)
Full-text articles assessed
for eligibility
(n = 32)
Full-text articles excluded,
with reasons
(n = 30)
Mainly due to an absence
of frailty measurement;
see Appendix A for a full
list of reasons.
Studies included in
research project
(n = 2)
From: Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group (2009). Preferred Reporting Items for Systematic Reviews and Meta-Analyses:
The PRISMA Statement. PLoS Med 6(7): e1000097. doi:10.1371/journal.pmed1000097
For more information, visit www.prisma-statement.org.

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3. Results
3.1 Number and type of studies included in the review
Two cohort studies (Landi et al. 2004, Brown et al. 2016) met all the inclusion criteria for
this review. The strengths and limitations of these studies are summarised in Table 3.1 and
Table 3.2 and a full overview of their details is given in Table 3.3 and Table 3.4.
3.2 Design and summary of the methodological quality of included studies
Study 1: Landi et al. (2004)
3.2 1a Aim and study setting
The aim of the study was to “explore the relationship between moderate-intensity physical
activity and the risk for all-cause mortality in a large population of frail and very old
persons living in the community.” The study uses data from an existing longitudinal,
multilinked database for 1998 to 2000 in Italy.
3.2 1b Cohort selection and cohort characteristics
As part of the Silver Network Home Care project (Landi et al. 1999), a national home care
program for frail elderly people in Italy, a database using the Minimum Data Set for Home
Care (MDS-HC) instrument (Morris et al. 1997) was formed. This was sponsored by the
Italian Gerontology and Geriatrics Society, the Italian General Practitioners Society, and
Pfizer Italy. This database includes a total of 3103 patients admitted to home care
programs in 12 home health agencies from 1998 to 2000.
These patients were considered frail based on assessments by trained staff (medical doctor
and nurses) who collected data according to the guidelines published in the MDS-HC
manual (Morris et al. 1997). From these 3103 frail elderly patients, a total of 346 were
excluded on the assumption that their conditions were incompatible with any kind of
physical activity, giving a final analysis sample of 2757 patients. Of the 346 patients
excluded from this study 103 were admitted to home care services with explicit diagnoses
of terminal illness and 243 were completely dependent on locomotion.
This sample of 2757 frail elderly community-dwelling patients were white and
predominately female (59%), with a mean age of 78.2 ± 9.5 years (>45% aged ≥80 years).

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3.2 1c Measurement of exposure
Participants were asked in “a single question about the average number of hours spent
during a standard week in domestic activities, such as light housework, cleaning house, or
gardening, or chosen physical activities, such as recreation, going out to shop or walk, or
light exercise.” This one question approach was based on recommendations of the MDS-
HC manual (Morris et al. 1996) and looking at these activities in hours per week was
based on guidelines of the American College of Sports Medicine (Pate et al. 1995) whose
recommendations are all in terms of units of time.
For those with limitations in verbal communication, the assessors were also instructed to
directly observe them and eventually to ask family members about their lifestyle.
All the patients were then divided into one of two groups based on their level of physical
activity: active (2 or more hours per week, N = 534) or sedentary (fewer than 2 hours per
week, N = 2223).
3.2 1d Measurement of outcome
In this study survival was measured from vital statistics given by General practitioners,
which were then confirmed by the National Death Registry.
The time of death was calculated from the date of the first MDS-HC assessment to the
date of death, and all the participants were followed up. Throughout the study a total of
442 (16%) participants died.
3.2 1e Follow-up of cohort, data analysis and controlling for confounding
The length of follow-up is inconsistently stated in this paper:
 “All participants were followed for at least 12 months.”
 “We evaluated all events that occurred through December 2001, with a mean
follow-up period of 10 months (range, 1–12 months).”
It appears most likely that the follow-up was a mean of 10 months as this is stated 3 times
throughout the paper, and the “at least” is probably intended to mean “up to” 12 months.
Cox proportional hazard analyses were carried out, adjusted for age, sex, baseline
comorbidity (cardiovascular diseases, pneumonia, cancer, stroke, diabetes, chronic

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obstructive pulmonary disease, renal failure, Parkinson’s disease, depression, delirium,
arthritis), functional ability (as measured by MDS ADL score), and cognitive impairment
(as measured by MDS cognitive performance scale score) and made Kaplan-Meier
survival curves for 3 age groups; younger than 70 years (A), 70 to 80 years (B), and older
than 80 years (C). Differences between these curves were tested using a log-rank test.
Crude and adjusted relative risks with accompanying 95% confidence intervals were also
given for these three age groups and the overall cohort. The adjusted relative risk was
adjusted for gender, physical and cognitive disability, cardiovascular diseases, pneumonia,
cancer, stroke, diabetes, chronic obstructive pulmonary disease, renal failure, Parkinson’s
disease, depression, delirium, and arthritis. A separate analysis was carried out excluding
patients who died in the first 90 days, under the assumption that this was due to an
underlying terminal illness. All statistical analyses were carried out using the SPSS
software (Chicago, IL).
3.2 1f Summary of the quality of the cohort study by Landi et al. 2004
Table 3.1: Summary of study quality: Landi et al. (2004) – cohort study
1) Cohort selection and recruitment
Strengths Large sample (N = 2757).
Frailty measured by doctors and nurses with MDS-HC guidelines.
All main confounding factors measured.
Limitations All white and mostly female therefore may not be generalisable to other groups.
2) Measurement of the exposure
Strengths Questions based on MDS-HC guidelines.
Those with verbal communication limitations were also included (observation, relatives)
Limitations Possibility of recall bias.
Differences between observed and recalled information.
3) Measurement of the outcome
Strengths Asked General Practitioner and confirmed by the National Death Registry.
Limitations -
4) Follow-up of the cohort, data analysis and controlling for confounding
Strengths No loss to follow-up.
Looks at survival curves as well as the Relative Risk.
Many main confounding factors were adjusted for.
Limitations Discrepancy in follow-up time reporting (x̅ = 10 months vs. all >12 months).
Short follow-up only catching 16% of deaths.
2 extra factors (age, functional ability) adjusted for in hazard analysis than Relative Risk.
Reverse causation – poorer health causing less physical activity and increased mortality.
BMI and self-rated health not included as confounders.
Residual confounding.
Unknown confounding factors.

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3.2.1g Overall assessment of the risk of bias
The assessment of physical activity in this trial is broad including all main relevant forms
and data has also been collected for those with verbal communication limitations. Since it
is based on memories of a standard week it could be susceptible to recall bias as well as a
tendency to overestimate due to the observer effect. Since those who had communication
difficulties were observed directly and relatives were asked this could have resulted in
non-uniform overestimations amongst the participants, in other words bias, between the
verbally limited observed individuals and the (probably healthier) self-reporters. However
the large sample size and no loss to follow-up both reduce the likelihood of bias.
In relation to confounding many main known confounders were taken into account but not
BMI and self-rated health. It is also odd how age and functional ability were adjusted for
in the hazard analysis but not in the risk analysis, and there is always the possible concerns
of residual confounding and unknown confounding factors.
Study 2: Brown et al. (2016)
3.2 2a Aim and study setting
The aim of the study was to “determine if physical activity and diet quality influence the
risk of mortality among a population-based sample of 1487 prefrail and frail older-adults
aged 65 years and older.” The study uses existing survey data for 1988 to 1994 in the
United States.
3.2 2b Cohort selection and cohort characteristics
The sample was taken from the Nutrition Examination Survey, 1988–1994 (NHANES III)
(National Center for Health Statistics 1994), which was a nationally representative sample
for the U.S.
This sample does not include “persons residing in nursing homes, members of the armed
forces, institutionalized persons, or U.S. nationals living abroad.” These individuals
probably make up a large proportion of the elderly population and may differ in important
ways such as physical fitness.
In this sample 4492 were aged 65 years and older, 3748 (83%) of these individuals had the
requisite measures necessary to determine frailty status, and 3551 (79%) also had the
necessary physical activity and diet quality data. Of these 3551 individuals 1487 where

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considered prefrail and frail making up the final analytic sample of the study. Their mean
age was 74.9 years and most were female (66.7%) and white (85.6%).
Frailty was defined in a way “that has been operationalized previously in the NHANES III
database” and was composed of 5 different criteria (Low weight for height, Slow walking
speed, Weakness, Exhaustion, Low levels of ambulatory activity). Details of these 5 frailty
criteria are as follows:
 Low weight for height (body mass index (BMI) ≤ 18.5 kg/m2
);
 Slow walking speed (slowest quintile adjusted for sex, in a timed 2.4-meter walk);
 Weakness (self-report of having any level of difficulty or inability to lift or carry
something as heavy as 4.5 kilograms);
 Exhaustion (self-report of having any level of difficulty or inability to walk from
one room to another on the same floor);
 Low levels of ambulatory activity including leisure time, occupational, household,
and transportation-related activity (a single self-report question of being less active
compared to men or women of a similar age).
Participants who met 1–2 of the 5 criteria were classified as prefrail (86.3%) and those
who met ≥3 were classified as frail (13.7%).
3.2 2c Measurement of exposure
The study looked at the exposures of physical activity and diet quality, but this review will
focus on findings relating to physical activity.
Participants were asked in a questionnaire if (and how many times) they did any of the
following 7 categories of leisure-time physical activities; jogging or running (≥1 mile),
riding a bicycle, swimming, aerobic or other dance, calisthenic or floor exercise,
gardening or yard work, and weight lifting, during the last month.
This information, based on recommendations by the American College of Sports Medicine
(Garber et al. 2011) was used to calculate physical activity in the form of number of bouts
per week, and all participants were measured in this way.

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Participants were put into one of 3 groups; Sedentary (0 bouts/week, 44.1%), Inactive (1–
4 bouts/week, 24.4%), or Active (≥5 bouts/week, 31.6%).
The secondary exposure of diet quality was measured using the Healthy Eating Index
(HEI) derived from a single 24-hour dietary recall using an automated interview process.
HEI scores <51, 51–80, and >80 were classified respectively as poor, fair, or good diet
quality (Ervin 2008).
3.2 2d Measurement of outcome
Deaths were measured using the “the National Death Index (NDI) database through
December 31, 2011.” “Participants were linked to the NDI database using probabilistic
matching that included 12 identifiers such as Social Security Number, sex, and date of
birth” based on Rogot et al. (1986).
The study the “National Center for Health Statistics found that 96.1% of deceased
participants and 99.4% of living participants were correctly classified using the
probabilistic matching algorithm (CDC link provided is now dead)” meaning there is a
small chance of error (≈5%). Throughout the study 1307 (87.2%) of the participants died.
3.2 2e Follow-up of cohort, data analysis and controlling for confounding
There was a median follow-up of 8.9 years (range: 0.25–22.0 years).
Cox proportional hazards regression models were used to estimate the hazard ratio (HR)
and the corresponding 95% confidence interval between physical activity and mortality.
Sample weights were incorporated into the statistical analyses to account for nonresponse
bias, and multistage sampling probabilities were used to provide estimates generalisable to
the U.S. population. Stata/SE v.14.1 statistical software was used for all analyses.
Estimates were adjusted for many confounding factors; Age, sex, race, body mass index,
smoking status, cognitive function, hypertension, hyperlipidemia, chronic obstructive
pulmonary disease, cancer, arthritis, myocardial infarction, stroke, heart failure, kidney
disease, self-rated health, hospitalization, falls, hemoglobin, c-reactive protein, glycated
hemoglobin, insulin, glucose, creatinine, frailty classification (frail v prefrail),
appendicular skeletal muscle mass, and gait speed.

14
3.2 1f Summary of the quality of the cohort study by Brown et al. 2016
Table 3.2: Summary of study quality: Brown et al. (2016) – cohort study
1) Cohort selection and recruitment
Strengths Large sample (N = 1487).
Frailty measure included 5 important aspects and was well linked with data set.
All known confounding factors measured.
Limitations 21% of survey participants not included due to missing data.
Mostly white and female therefore may not be generalisable to other groups.
2) Measurement of the exposure
Strengths -
Limitations Recall bias very likely (1 month period).
Distance criteria for running/jogging only.
Absence of household work or walking as forms of physical activity.
No measurement of physical activity duration or energy expenditure.
3) Measurement of the outcome
Strengths National Death Index database is a reliable source of data.
Limitations A small chance of error (≈5%) since a matching algorithm is used.
4) Follow-up of the cohort, data analysis and controlling for confounding
Strengths No loss to follow-up
Long follow-up (0.25–22.0 years; median 8.9 years) catching 87.2% of deaths.
Statistical efforts made to provide estimates generalisable to the U.S. population
Limitations Reverse causation – poorer health causing less physical activity and increased mortality.
Residual confounding.
Unknown confounding factors.
3.2.1g Overall assessment of the risk of bias
Since these results relied heavily on the memory of elderly individuals going back a whole
month, recall bias may have been a serious problem. Recalling of a shorter period (e.g. 1
week) would have reduced this issue, alternatively an exercise diary may have been used
to estimate accurate rates but this may have resulted the observation effect. However the
large sample size and long follow-up without loss both reduce the likelihood of bias.
Another problem is the possibility of large discrepancies in energy expenditure between
the different “leisure-time” physical activities given, for example running over a mile
compared to gardening, and this is not acknowledged or taken into account. Additionally
there is a distance criterion of ≥1 mile specified for jogging/running, but no distance
criterion for any of the other physical activities such as cycling or swimming (at least this
is how it is reported).
It also does not make sense to limit physical activity to just “leisure-time” activities with a
recent large study (Huerta et al. 2016) finding household physical activity to be associated

15
with the largest mortality reductions, and yet for some reason “gardening and yard work”
is included. Walking is also not included as a form of physical activity in this study.
The idea of defining physical activity by the number of bouts per week is based on
guidelines by the American College of Sports Medicine “for adults of all ages” from the
paper Garber et al. (2011), but no measurement of physical activity duration is made.
While we are looking at participation in physical activities rather than people’s physical
stamina, duration is still an important aspect and ideally should have been measured and
taken into account.
In summary the potential methodological issues in this study are large with the distance
criteria for running/jogging only, absence of household work or walking as forms of
physical activity, and no measurement of physical activity duration or energy expenditure.
For these reasons the results are possibly highly biased and unrepresentative of lighter
forms of physical activity which may still infer significant benefits, especially in the case
of frail elderly individuals.

16
3.3 Results: Associations between physical activity, dietary influence, and mortality in frail elderly
The relative risks and hazard ratios for the association between physical activity and mortality in the two studies
included in this review are presented in Table 3.3 (below) as well as the influence of diet.
Table 3.3: Results of cohort studies by Landi et al. (2004) and Brown et al. (2016)
Study ID Group Relative Risk
Crude (95% CI)
Relative Risk
Adjusted (95% CI)
Survival curve
Log-rank p-value
Landi et al. (2004)
Total 0.43 (0.31–0.60) 0.51 (0.35–0.73) -
< 70 years 0.38 (0.19–0.74) 0.48 (0.21–1.11) 0.001
70-80 years 0.46 (0.26–0.81) 0.50 (0.26–0.97) 0.001
>80 years 0.46 (0.28–0.75) 0.55 (0.32–0.95) 0.001
< 70 years* 0.63 (0.29–1.33) -
70-80 years* 0.51 (0.26–0.98) -
>80 years* 0.61 (0.39–0.99) -
*Excluding patients who died in the first 90 days; not specified if these Relative Risks were crude or adjusted
Study ID Group Hazard Ratio
Adjusted age & sex
(95% CI)
Hazard Ratio
Adjusted all factors
(95% CI)
Survival curve
Log-rank p-value
Brown et al. 2016
Inactive 0.74 (0.60–0.91) 0.76 (0.58–0.98)*
0.001
Active 0.73 (0.60–0.89) 0.66 (0.51–0.86)*
Fair Diet 0.69 (0.55–0.86) 0.74 (0.52–1.05)*
0.002
Good Diet 0.67 (0.52–0.87) 0.67 (0.44–1.00)*
Poor Diet Fair Diet Good Diet
Sedentary (reference) 0.71 (0.51–0.97) 0.77 (0.55–1.07)
Inactive 0.62 (0.40–0.97) 1.22 (0.72–2.04) 1.18 (0.65–2.14)
Active 1.20 (0.78–1.85) 0.63 (0.39–1.03) 0.50 (0.29–0.87)
*Values very similar (still significant or insignificant) when also adjusted for either diet or physical activity
Landi et al. (2004)
The crude relative risk for those who were active compared to sedentary was 0.43 (95%
CI 0.31–0.60) for the overall cohort, 0.38 (95% CI 0.19–0.74) for those < 70 years, 0.46
(95% CI 0.26–0.81) for those 70-80 years and 0.46 (95% CI 0.28–0.75) for those over >80
years. Thus the crude relative risk was significant for all age groups of the elderly sample.
The adjusted relative risk for those who were active compared to sedentary was 0.51 (95%
(95% CI 0.26–0.97) for those 70-80 years and 0.55 (95% CI 0.32–0.95) for those over >80
years. When adjusted the relative risk remained significant for all age groups except those
under 70 years (i.e. between 68 and 70 years old).
When excluding participants who died in the first 90 days the results were 0.63 (95% CI
0.29–1.33), 0.51 (95% CI 0.26–0.98), and 0.61 (95% CI 0.39–0.99) for the age groups <
70 years, 70-80 years, and >80 years respectively. Thus the relative risk was still
significant for all age groups except those under 70 years (i.e. between 68 and 70 years
old) when early deaths were excluded.

17
Finally in the Kaplan-Meier survival curves the log-rank p-value for the hazard ratios was
0.001 for all age groups; < 70 years, 70-80 years, and >80 years. Therefore there is a
statistically significant difference in survival between those who are active and those that
are sedentary in all age groups when considering hazard ratios.
Brown et al. 2016
The age and sex adjusted hazard ratio for those who were inactive compared to sedentary
was 0.74 (95% CI 0.60–0.91) and 0.73 (95% CI 0.60–0.89) for those who were active
compared to sedentary. Thus being active or inactive instead of sedentary significantly
reduced the likelihood of mortality in frail elderly people when adjusted for differences in
age and sex.
The fully adjusted hazard ratio for those who were inactive compared to sedentary was
0.76 (95% CI 0.58–0.98) and 0.66 (95% CI 0.51–0.86) for those who were active
compared to sedentary. When adjusted for all factors being active or inactive instead of
sedentary still significantly reduced the likelihood of mortality in frail elderly people and
this also remained the case when adjusted for diet.
The log-rank p-value was 0.001 for the trend across physical activity levels; sedentary,
inactive and active. Therefore this trend is statistically significant.
The age and sex adjusted hazard ratios for those with a fair diet compared to a poor diet
was 0.69 (95% CI 0.55–0.86) and 0.67 (95%CI 0.52–0.87) for those with a good diet
compared to a poor diet. However when adjusted for all confounding factors these hazard
ratios lost statistical significance becoming 0.74 (0.52–1.05) and 0.67 (0.44–1.00)
respectively. This remained the case when adjusted for physical activity as well.
The log-rank p-value was 0.001 for the trend across dietary levels; poor, fair and good.
Therefore this trend is statistically significant.
For the interaction between activity level and diet compared to those who were sedentary
and had a poor diet there were significant reductions in mortality for those who were
sedentary with a fair diet [0.71 (0.51–0.97)], inactive with a poor diet [0.62 (0.40–0.97)],
and active with a good diet [0.50 (0.29–0.87)].

18
Results Tables
Landi et al. (2004)
Table 3.4: Results Table for study 1
Study ID Landi et al. (2004)
Study Objective To “explore the relationship between moderate-intensity physical activity and the risk for
all-cause mortality in a large population of frail and very old persons living in the
community.”
Study Setting Italy 1998 to 2000.
Selection of Cohort Sample from an existing longitudinal, multilinked database collected using the Minimum
Data Set for Home Care (MDS-HC) instrument as part of the Silver Network Home Care
project.
Frailty was diagnosed by medical doctors and nurses and this provided a sample of 2757
frail elderly community-dwelling patients who were white, predominately female (59%),
and with a mean age of 78.2 ± 9.5 years (>45% aged ≥80 years).
Exposure
Measurement
A single question about the average number of hours spent during a standard week in
domestic activities, such as light housework, cleaning house, or gardening, or chosen
physical activities, such as recreation, going out to shop or walk, or light exercise.
All the patients were then divided into one of two groups based on their level of physical
activity: active (2 or more hours per week, N = 534) or sedentary (fewer than 2 hours per
week, N = 2223).
Statistical analysis
and control for
confounding
Measured crude and adjusted relative risks for the total cohort and for each of the age
groups < 70 years, 70-80 years, and >80 years. Also did a separate analysis excluding
participants who died in the first 90 days (assuming underlying terminal illness).
Kaplan-Meier survival curves were also made for each of the age groups < 70 years, 70-
80 years, and >80 years, and a log-rank p-value was calculated for their trend.
All statistical analyses were carried out using the SPSS software (Chicago, IL).
Results The crude relative risk for those who were active compared to sedentary was 0.43 (95%
(95% CI 0.26–0.81) for those 70-80 years and 0.46 (95% CI 0.28–0.75) for those over
>80 years.
The adjusted relative risk for those who were active compared to sedentary was 0.51
(95% CI 0.35–0.73) for the overall cohort, 0.48 (95% CI 0.21–1.11) for those < 70 years,
0.50 (95% CI 0.26–0.97) for those 70-80 years and 0.55 (95% CI 0.32–0.95) for those
over >80 years.
When excluding participants who died in the first 90 days the results were 0.63 (95% CI
0.29–1.33), 0.51 (95% CI 0.26–0.98), and 0.61 (95% CI 0.39–0.99) for the age groups <
70 years, 70-80 years, and >80 years respectively.
Finally in the Kaplan-Meier survival curves the log-rank p-value for the hazard ratios
was 0.001 for all age groups; < 70 years, 70-80 years, and >80 years.
Authors’
Conclusions
“Physical activity is associated with a significantly lower risk of all-cause mortality. The
current findings support the possibility that moderate-intensity physical activity has an
independent effect on survival even among frail and old persons.”

19
Brown et al. (2016)
Table 3.5: Results Table for study 2
Study ID Brown et al. (2016)
Study Objective To “determine if physical activity and diet quality influence the risk of mortality among a
prefrail and frail older-adults aged 65 years and older.”
Study Setting USA sample 1988 to 1994, and additional follow-up.
Selection of Cohort Sample from existing survey data of the Nutrition Examination Survey, 1988–1994
(NHANES III).
This provided a sample of 4492 people aged 65 years and older, but only 3551 (79%) had
the necessary data. Of these 3551 individuals 1487 where considered prefrail and frail
making up the final analytic sample of the study. Their mean age was 74.9 years.
There were 5 frailty criteria; Low weight for height, Slow walking speed, Weakness,
Exhaustion, and Low levels of ambulatory activity. Participants who met 1–2 of the
criteria were classified as prefrail (86.3%) and those who met ≥3 were classified as frail
(13.7%). This sample was predominantly female (66.7%) and white (85.6%).
Exposure
Measurement
Questionnaire asking how many times they engaged in any of the following leisure-time
physical activities; jogging or running (≥1 mile), riding a bicycle, swimming, aerobic or
other dance, calisthenic or floor exercise, gardening or yard work, and weight lifting,
during the last month.
Also assessed diet and how this modified the effects of physical activity on mortality.
All participants were put into one of 3 groups; Sedentary (0 bouts/week, 44.1%), Inactive
(1–4 bouts/week, 24.4%), or Active (≥5 bouts/week, 31.6%).
Statistical analysis
and control for
confounding
Cox proportional hazards regression models were used to estimate the hazard ratio (HR)
and corresponding 95% confidence interval between physical activity and mortality for
individuals who were active compared to sedentary and inactive compared to sedentary.
These estimates were adjusted for age and sex in one analysis and adjusted for all known
confounders in another analysis.
Log-rank p-value was calculated for the hazard ratio trend.
Stata/SE v.14.1 statistical software was used for all analyses.
Results The age and sex adjusted hazard ratio for those who were inactive compared to sedentary
was 0.74 (95% CI 0.60–0.91) and 0.73 (95% CI 0.60–0.89) for those who were active
compared to sedentary. Thus being active or inactive instead of sedentary significantly
reduced the likelihood of mortality in frail elderly people when adjusted for differences
in age and sex.
The fully adjusted hazard ratio for those who were inactive compared to sedentary was
0.76 (95% CI 0.58–0.98) and 0.66 (95% CI 0.51–0.86) for those who were active
compared to sedentary.
The log-rank p-value was 0.001 for the trend across physical activity levels; sedentary,
inactive and active.

20
The age and sex adjusted hazard ratio for those with a fair diet compared to a poor diet
was 0.69 (95% CI 0.55–0.86) and 0.67 (95%CI 0.52–0.87) for those with a good diet
compared to a poor diet. However when adjusted for all confounding factors these hazard
ratios lost statistical significance becoming 0.74 (0.52–1.05) and 0.67 (0.44–1.00)
respectively. This remained the case when adjusted for physical activity as well.
The log-rank p-value was 0.001 for the trend across dietary levels; poor, fair and good.
For the interaction between activity level and diet compared to those who were sedentary
and had a poor diet there were significant reductions in mortality for those who were
sedentary with a fair diet [0.71 (0.51–0.97)], inactive with a poor diet [0.62 (0.40–0.97)],
and active with a good diet [0.50 (0.29–0.87)].
Authors’
Conclusions
“Participation in physical activity and consumption of a healthy diet is associated with a
lower risk of mortality among prefrail and frail older adults.”

21
Discussion
Both studies found strong statistically significant relationships between physical activity
and reductions in all-cause mortality for community-dwelling frail elderly people. Brown
et al. (2016) found that adjusting for confounders those who were active compared to
sedentary had a 34% lower risk of mortality [HR 0.66 (95% CI 0.51–0.86)] and those who
were inactive compared to sedentary had a 24% lower risk of mortality [HR 0.76 (95% CI
0.58–0.98)]. Landi et al. (2004) found that adjusting for confounders those who were
active compared to sedentary had a 49% lower risk of mortality [RR 0.51 (95% CI 0.35–
0.73)] and this relationship was also true for those over 80 years of age with a 45% lower
risk of mortality [RR 0.55 (95% CI 0.32–0.95)].
These findings are consistent with a large volume of previous research showing that
exercise and physical activity are associated with reduced mortality in adults (Samitz et al.
2011, Huerta et al. 2016), as well as over 60s (Hupin et al. 2015), over 75s (Rizzuto et al.
2012), and in dizygotic twins (Kujala et al. 1998, Waller et al. 2010). The benefits appear
to outweigh the risks and there are a growing number of RCTs showing that physical
activity can improve mobility and reduce falls in the elderly (Thomas et al. 2010, Pahor et
al. 2014, Gill et al. 2016). Given the findings of this review these benefits appear to be
also applicable to those with pre-existing frailty symptoms.
However despite the significant associations noted in this review, causal inferences
relating to physical activity and mortality are still difficult to make with no association
ever being observed in the case of monozygotic twins (Kujala et al. 1998, Waller et al.
2010) and temporality being extremely difficult to determine due to possible confounding
from physical fitness. In other words taking the premise that improvements in health
increase life expectancy, is being more physically active the cause of improved health, or
is having better underlying health (perhaps undetected) causing the participation in
physical activity?
Such a question rests on the very edge of what can be addressed by scientific method and
current apparatus however, beyond the initial will to participate, physical activity appears
to be a clear causal factor resulting in improvements in fitness and health. This can be
noted in a number of RCTs (Fujimoto et al. 2010, Thomas et al. 2010, Naci and Ioannidis
2013) and there is also previous research suggesting that physical activity or energy

22
expenditure is beneficial within all levels of measured physical fitness (Blair et al. 2001,
Myers et al. 2004, Myers et al. 2015).
However this interplay between physical activity, energy expenditure and physical fitness
brings up another important distinction, the difference between physical activity and mere
energy expenditure. Physical activity as understood in the context of this review is being
involved in something that requires physical movement such as walking or even cleaning
and these are activities with both interpersonal and social dimensions in addition to the
expenditure of energy. In fact the social aspect of activities means that physical activity
can be as important mentally as physically and Middleton et al. (2008) found that over a 5
year follow-up elderly who were physically active had significantly less cognitive decline.
Differences in conceptualising what physical activity or exercise includes are also
important since they can lead to fundamentally different measurement processes as seen in
the two studies in this report (see sections 3.2 1c and 3.3 2c) as well as the realisation that
different kinds of physical activity will probably have very different physical effects. For
example in relation to reduced mortality Huerta et al. (2016) found the largest significant
association for household physical activity, a significant association for leisure time
physical activity in women only, and no association for work time sedentariness. As well
as possible social aspects there are numerous biological explanations for how being
physically active increases health and thus reduces mortality.
In fact exercise can lead to healthier body composition, enhancement of lipid lipoprotein
profiles, improved glucose homeostasis and insulin sensitivity, reduced blood pressure,
reduced systemic inflammation (possibly through a reduction of inflammatory mediators
such as C-reactive protein), decreasing of blood coagulation, augmented cardiac function,
increasing balance/stability, and enhanced endothelial function (Warburton et al. 2006).
Endurance exercise can also enhance or reverse reductions in organ functional capacity;
and strength based training can strengthen bones and maintain muscle mass (Mazzeo et al.
1998, Fries 2000). In the case of frail elderly this is additionally supported by a Japanese
randomised control trial (Fujimoto et al. 2010) showing improvements in fitness from the
Tai Chi Yuttari-exercise, although no significant difference was observed in mortality risk.

23
This review as discussed above does find a significant association between physical
activity and reduced all-cause mortality in frail community-dwelling elderly however due
to possible bias, some inconsistent reporting of procedures, and a problematic
measurement of physical activity these findings should be interpreted cautiously.
This review also incorporated the influence between diet quality and physical activity in
the reduction of mortality risk (Brown et al. 2016) and significant reductions were
observed only for those who were 1) sedentary and a fair diet, 2) inactive and a poor diet,
or 3) active and a good diet. However the surprising cases 1) and 2) were only barely
statistically significant and the good diets may also have been confounded by
overconsumption. More research is needed into these interactions.
Brown et al. (2016) also appears to indicate a dose response relationship between physical
activity and mortality in frail elderly. However the confidence intervals between these
groups overlap.
Limitations of this structured literature review
This review has a number of important limitations that should be considered.
1. Only cohort studies were located so it is only possible to assess association, not
causation. Given the large volume of previous support for a temporal relationship
and accompanying biological plausibility it seems reasonable to infer that the
relationship is causal but such assumptions should be made cautiously. As
discussed already underlying physical fitness could be a confounder and many
physical activities vary in terms of energy expenditures, physiological elements,
and social dimensions making both inferences and generalisation problematic.
RCTs are needed to properly test causation but may not be generalisable or ethical.
2. Only 2 databases were searched; PubMed and Google Scholar. While Google
Scholar is the largest database it is not all inclusive and due to features of the
search algorisms and indexing issues relevant results could be left out even when
contained within the database. I noticed this problem on PubMed where using the
“human only” limit would remove Brown et al. (2016) and other “human” studies
from the search hits.

24
3. The English language restriction also restricted both the number of search hits and
what search hits could be used in this review (as a number of studies with only the
abstract in English slipped through). This meant that studies such as Fujimoto et al.
(2010) could not be examined further and could not be sufficiently
methodologically appraised for inclusion beyond discussion purposes within this
review. This is a shame as the above study was a relevant RTC and there could
have been many other relevant studies that went unnoticed due to their publication
language.
4. Generalisability of the study samples in this review could be considered potentially
limited. Both studies (Italy and the United States) contained a sample that was
composed predominately of white females. Females tend to live longer on average
in nearly every country so it would be expected that there would be a greater
number of females within any elderly population and both studies adjusted for
differences in sex. However since most were white and mainly from “probably”
affluent areas there could be difficulty in comparing this to areas with different
ethnic and social demographics. Samples were also community based and may not
be generalisable to those in hospitals or nursing homes, etc.
5. Carried out by one person. While others offered me some very helpful information
and advice, all research and writing in this review was a solo effort on my part and
any research done by just one author by its very nature has an increased risk of
mistakes, omission and misinterpretation.

25
Conclusions
Implications for practice
Despite its limitations this review supports the continued recommendation of physical
activity for frail elderly individuals. It could be an effective and inexpensive method of
increasing health and wellbeing within this growing and vulnerable population subgroup.
Recommendations for future research
Research into the different forms of physical activity in the elderly may be helpful. RCTs
would provide clearer results although at this stage I feel they will have to compare one
form of physical activity to another in order to be ethically justifiable. A previous study
(Zhao et al. 2013) found that muscle-strengthening activity ≥2 times/week may provide
additional benefits among insufficiently active adults and this is definitely worthy of
further examination.

26
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