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Unintended Weight Loss in Older Adults

UWL: Nutritional Status (2009)


Margetts BM, Thompson RL, Elia M, Jackson AA. Prevalence of risk of undernutiriton is associated with poor health status in older people in the UK. Eur J Clin Nutr. 2003; 57: 69-74.

PubMed ID: 12548299
Study Design:
Cross-Sectional Study
D - Click here for explanation of classification scheme.
Quality Rating:
Neutral NEUTRAL: See Quality Criteria Checklist below.
Research Purpose:

To use the Malnutrition Advisory Group criteria to determine the prevalence of the risk of under-nutrition in a representative sample of older people in the UK and to assess whether there was any relationship between risk of under-nutrition and reported health status or demographic characteristics.

Inclusion Criteria:
  • Free-living and institutionalized people in the UK
  • Aged 65 and older. 
Exclusion Criteria:

Not specified.

Description of Study Protocol:


  • Free-living participants were sampled by postal code, with one person per household selected to identify approximately equal numbers of people for each of three age groups
  • Institutionalized subjects were recruited in a two-stage process: Residential and nursing homes were randomly selected within each of the areas surveyed for the free-living sample and a random sample drawn from the institutions that agreed to cooperate.  


Secondary analysis of cross-sectional data. Subjects were divided into three groups (high, medium or low risk) according to the MAG tool and the prevalence of under-nutrition assessed.      

Statistical Analysis

  • Means and 95% confidence intervals were used to describe blood analytes and simple proportions were used to describe differences between under-nutrition risk groups.
  • Binary logistic regression was used to assess the risk of being in either the medium or high risk of under-nutrition compared to the low-risk group for a range of categorical variables.
Data Collection Summary:

Timing of Measurements

 Single measurements except for intake which was obtained for a four-day period. 

Dependent Variables

  • Albumin from an anticubital blood sample
  • Fat soluble vitamins using HPLC
  • Vitamin C from a plasma sample using a centrifugal analyzer with fluorescence analyzer
  • RBC folate using microbiological assay and chloramphenical-resistant L. casei
  • Zinc in plasma using a centrifugal analyzer
  • Dietary intake using a four-day weighed dietary intake
  • Height was measured using a stadiometer
  • Weight without shoes and heavy garments
  • Weight loss within the previous six months by self-report.

Independent Variables

  • Health and demographic characteristics
  • Individuals were asked about their health history, long-standing illnesses and hospital admission within the previous 12 months.


Description of Actual Data Sample:
  • Initial N: The total sample was 2,172 individuals, of whom 1,632 responded; 1,368 provided anthropometric data and 1,276 provided blood samples
  • Attrition (final N): 1,368 providing anthropometric data and 1,276 provided blood samples
  • Age: 65 or greater
  • Other relevant demographics: 1,128 were free living and 240 lived in an institution
  • Location: United Kingdom.
Summary of Results:


Proportion of Subjects with Low BMI, Weight Loss in Last Six Months and Proportion of Subjects Defined as at Risk of Under-nutrition





Body mass index (BMI), kg/m2


Less than 18.5



Less than 20



Reporting weight loss in last six months




Those with weight loss


Less than 1.4kg



1.4 to 3.2kg



More than 3.2kg



Risk of under-nutrition*











*Malnutrition was assigned based on the MAG tool; high risk was BMI less than 18.5 or BMI 18.5 to 20.0 plus weight loss of 3.2kg or more, or BMI more than 20.0 plus weight loss of more than 6.4kg; medium risk was BMI 18.5 to 20.0 plus weight loss less than 3.2kg (unless no long-term illness and no weight loss) or BMI more than 20 and weight loss 3.2 to 6.4kg; low risk was BMI more than 20 and no weight loss (less than 5% body weight).

Percentage Distribution at Risk of Under-nutrition by Gender, Age Group, Domicile, Health Status, Long-standing Illness and Hospitalization

Variable (N; percentage)

Risk of under nutrition






   Males (N=694; 50.7)

   Females (N=674; 49.3)


88.2 (51.8)*

84.6 (48.2)


5.6 (42.9)

7.7 (57.1)


6.2 (45.3)

7.7 (54.7)

Age group

    65 to 74 (N=507; 37.1)

    75 to 84 (N=527; 38.5)

    85 + (n=240; 17.5)


89.7 (38.5)

85.2 (38.0)

83.2 (23.5)


5.3 (29.7)

6.8 (39.6)

8.4 (30.8)


4.9 (26.3)

8.0 (44.2)

8.4 (29.5)


    Free living



87.9 (83.9)

79.2 (16.1)


6.3 (78.0)

8.3 (22.0)


5.8 (68.4)

12.5 (31.6)

Health status

    Good/very good (N=854; 62.7) 

   Fair (N=433; 31.8)

    Bad/very bad (N=76; 5.6)


89.2 (64.7)

83.4 (30.6)

72.4 (4.7)


6.3 (59.3)

7.4 (35.2)

6.6 (5.5)


4.4 (40.4)

 9.2 (42.6)

21.1 (17.0)

Long-standing illness

    Yes (N=279; 20.4)

    No (N=407; 29.8)



83.5 (67.8)

93.4 (32.2)


5.7 (17.6)

6.9 (82.4)


14.3 (42.6)

 5.0 (57.4)

* represents column percentage within each variable.


Binary Logistic Regression of Risk Factors for Risk of Under-nutrition (High- and Medium-risks Combined); Each Odds Ratio Adjusted for the Effects of Gender, Age, Region, Domicile, Reported Health Status, Long-standing Illness, Hospitalized; Low Risk as Reference Category


Variable                                                                        Odds Ratio (95% Confidence Variable)


Being in hospital in last year (yes vs. no)                     1.83 (1.06 to 3.16)

Institution vs. free living                                                   2.17 (1.22 to 3.88)

Longstanding illness (yes vs. no)                                   2.34 (1.20 to 4.58)

Age (85 or older vs. 65 to 74 years)                              2.64 (1.54 to 5.11)


Health (bad vs. good)                                                      2.82 (1.25 to 6.38)

Long-standing illness (yes vs. no)                                  2.98 (1.58 to 5.62)


Mean (95% Confidence Intervals) Serum Levels by Risk of Under-nutrition


Serum Levels

Risk of Under-nutrition





Albumin (g per dL)

42.5 (42.2 to 43.9)


41.6 (40.0 to 43.1)


39.7 (38.0 to 41.4)*

Vitamin D (nmol per L)

52.1 (50.4 to 53.7)

43.8 (37.7 to 49.8)

42.0 (37.0 to 47.1)*

Vitamin E (μmol per L)

36.6 (35.9 to 37.4)


33.1(30.7 to 35.6)


32.4 (29.6 to 35.2)*


Vitamin C (μmol per L)

40.6 (39.1 to 42.2)


31.5 (25.1 to 37.9)


26.8 (20.9 to 32.6)*


Zinc (μmol per L)

14.1 (14.0 to 14.2)

13.2 (12.6 to 13.8)

12.8 (12.2  to 13.4)*

Vitamin A (μmol per L)

2.20 (2.16 to 2.24)


1.97 (1.82 to 2.11)


2.02 (1.85 to 2.19)


RBC Folate (nmol per L)

499 (478 to 517)


466 (408 to 525)

1504 (435 to 574)

Ferritin (mcg per L)

100.4 (92.9 to 108.0)

98.4 (76.8 to 120.1)

121.0 (91.1 to 150.8)

High-risk group statistically significantly different from low-risk group (LSD ANOVA).

Other Findings

  • About 14% (21% in those living in institutions) were at medium or high risk of under-nutrition based on a composite measure of low body mass index and recent reported weight loss
  • Having a long-standing illness was associated with a statistically significant increased risk of under-nutrition (men: odds ratio, 2.34; 95% confidence interval, 1.20 to 4.58; women: 2.98, 95% confidence interval, 1.58 to 5.62)
  • The risk of under-nutrition increased: In women reporting bad or very bad health status, in men living in northern England and Scotland, for those aged 85 years and older, for those hospitalized in the last year and those living in an institution
  • Lower consumption of energy, meat products or fruit and vegetables and lower blood measures of zinc, vitamins A, D, E and C were associated with statistically significantly increased risk of under-nutrition.
Author Conclusion:

A substantial portion of the older population of the UK is at risk of undernutrition. High-risk subjects are more likely to have poorer health status. It is unlikely that the individuals at high risk are being detected currently, and therefore effective care is not being provided, either in the community or in institutions. 

Funding Source:
Government: Partly funded by a grant from the Department of Health
Reviewer Comments:

Nationally representative sample of older people living in the UK; however, authors note that sampling or information biases may be present in this study. Data on weight loss based on self-report.

Quality Criteria Checklist: Primary Research
Relevance Questions
  1. Would implementing the studied intervention or procedure (if found successful) result in improved outcomes for the patients/clients/population group? (Not Applicable for some epidemiological studies) N/A
  2. Did the authors study an outcome (dependent variable) or topic that the patients/clients/population group would care about? Yes
  3. Is the focus of the intervention or procedure (independent variable) or topic of study a common issue of concern to dieteticspractice? Yes
  4. Is the intervention or procedure feasible? (NA for some epidemiological studies) N/A
Validity Questions
1. Was the research question clearly stated? Yes
  1.1. Was (were) the specific intervention(s) or procedure(s) [independent variable(s)] identified? Yes
  1.2. Was (were) the outcome(s) [dependent variable(s)] clearly indicated? Yes
  1.3. Were the target population and setting specified? Yes
2. Was the selection of study subjects/patients free from bias? ???
  2.1. Were inclusion/exclusion criteria specified (e.g., risk, point in disease progression, diagnostic or prognosis criteria), and with sufficient detail and without omitting criteria critical to the study? ???
  2.2. Were criteria applied equally to all study groups? Yes
  2.3. Were health, demographics, and other characteristics of subjects described? Yes
  2.4. Were the subjects/patients a representative sample of the relevant population? ???
3. Were study groups comparable? Yes
  3.1. Was the method of assigning subjects/patients to groups described and unbiased? (Method of randomization identified if RCT) Yes
  3.2. Were distribution of disease status, prognostic factors, and other factors (e.g., demographics) similar across study groups at baseline? Yes
  3.3. Were concurrent controls or comparisons used? (Concurrent preferred over historical control or comparison groups.) N/A
  3.4. If cohort study or cross-sectional study, were groups comparable on important confounding factors and/or were preexisting differences accounted for by using appropriate adjustments in statistical analysis? Yes
  3.5. If case control study, were potential confounding factors comparable for cases and controls? (If case series or trial with subjects serving as own control, this criterion is not applicable.) N/A
  3.6. If diagnostic test, was there an independent blind comparison with an appropriate reference standard (e.g., "gold standard")? N/A
4. Was method of handling withdrawals described? Yes
  4.1. Were follow-up methods described and the same for all groups? Yes
  4.2. Was the number, characteristics of withdrawals (i.e., dropouts, lost to follow up, attrition rate) and/or response rate (cross-sectional studies) described for each group? (Follow up goal for a strong study is 80%.) Yes
  4.3. Were all enrolled subjects/patients (in the original sample) accounted for? Yes
  4.4. Were reasons for withdrawals similar across groups? N/A
  4.5. If diagnostic test, was decision to perform reference test not dependent on results of test under study? N/A
5. Was blinding used to prevent introduction of bias? N/A
  5.1. In intervention study, were subjects, clinicians/practitioners, and investigators blinded to treatment group, as appropriate? N/A
  5.2. Were data collectors blinded for outcomes assessment? (If outcome is measured using an objective test, such as a lab value, this criterion is assumed to be met.) N/A
  5.3. In cohort study or cross-sectional study, were measurements of outcomes and risk factors blinded? ???
  5.4. In case control study, was case definition explicit and case ascertainment not influenced by exposure status? N/A
  5.5. In diagnostic study, were test results blinded to patient history and other test results? N/A
6. Were intervention/therapeutic regimens/exposure factor or procedure and any comparison(s) described in detail? Were interveningfactors described? Yes
  6.1. In RCT or other intervention trial, were protocols described for all regimens studied? N/A
  6.2. In observational study, were interventions, study settings, and clinicians/provider described? Yes
  6.3. Was the intensity and duration of the intervention or exposure factor sufficient to produce a meaningful effect? N/A
  6.4. Was the amount of exposure and, if relevant, subject/patient compliance measured? N/A
  6.5. Were co-interventions (e.g., ancillary treatments, other therapies) described? N/A
  6.6. Were extra or unplanned treatments described? N/A
  6.7. Was the information for 6.4, 6.5, and 6.6 assessed the same way for all groups? N/A
  6.8. In diagnostic study, were details of test administration and replication sufficient? N/A
7. Were outcomes clearly defined and the measurements valid and reliable? ???
  7.1. Were primary and secondary endpoints described and relevant to the question? Yes
  7.2. Were nutrition measures appropriate to question and outcomes of concern? Yes
  7.3. Was the period of follow-up long enough for important outcome(s) to occur? N/A
  7.4. Were the observations and measurements based on standard, valid, and reliable data collection instruments/tests/procedures? ???
  7.5. Was the measurement of effect at an appropriate level of precision? Yes
  7.6. Were other factors accounted for (measured) that could affect outcomes? Yes
  7.7. Were the measurements conducted consistently across groups? N/A
8. Was the statistical analysis appropriate for the study design and type of outcome indicators? Yes
  8.1. Were statistical analyses adequately described and the results reported appropriately? Yes
  8.2. Were correct statistical tests used and assumptions of test not violated? Yes
  8.3. Were statistics reported with levels of significance and/or confidence intervals? Yes
  8.4. Was "intent to treat" analysis of outcomes done (and as appropriate, was there an analysis of outcomes for those maximally exposed or a dose-response analysis)? N/A
  8.5. Were adequate adjustments made for effects of confounding factors that might have affected the outcomes (e.g., multivariate analyses)? Yes
  8.6. Was clinical significance as well as statistical significance reported? No
  8.7. If negative findings, was a power calculation reported to address type 2 error? N/A
9. Are conclusions supported by results with biases and limitations taken into consideration? Yes
  9.1. Is there a discussion of findings? Yes
  9.2. Are biases and study limitations identified and discussed? Yes
10. Is bias due to study's funding or sponsorship unlikely? Yes
  10.1. Were sources of funding and investigators' affiliations described? Yes
  10.2. Was the study free from apparent conflict of interest? Yes