The effects of single and a combination of determinants of anaemia in the very old: results from the TULIPS consortium

The Leiden 85-plus Study recruited 85-year-old inhabitants in Leiden, the Netherlands. From September 1997 through September 1999, 705 inhabitants reached the age of 85 years and were eligible for participation in the study. Subjects were visited annually (at ages 85–90 years for 5 years) at their place of residence for face-to-face interviews and cognitive tests. Blood samples were taken according to predefined protocols under non-fasting conditions. The medical history was obtained from the participants, or partners and caregivers in memory-impaired subjects. Pharmacy records were studied annually, and participants were also interviewed to evaluate the use of (over-the-counter) supplements. The Medical Ethical Committee of the Leiden University Medical Center approved the study, and informed consent was obtained from all subjects or their guardian for cognitively impaired subjects [17].

The Life and Living in Advanced Age (LiLACS NZ) is a population-based study of two cohorts: Māori and non-Māori in advanced age in New Zealand. Participants were living in the Bay of Plenty and were born between 1 January, 1925 and 31 December, 1925 for non-Māori (85 years) and between 1920 and 1930 for Māori (80–90 years old) [18, 19]. At baseline, participants were interviewed using a comprehensive questionnaire, conducted by trained interviewers, and had a health assessment conducted by a trained nurse. Blood samples were collected at baseline after an overnight fasting. Information about medication and supplement intake was collected. A simplified version of the questionnaire was made available for those unable to do the comprehensive one [18]. Ethical approval for the LiLACS NZ was granted by the Northern X Regional Ethics Committee (NTX 09/09/088) in December 2009 and written informed consent was obtained from all participants for each stage of the study [19].

The Newcastle 85+ study recruited individuals turning 85 years old in 2006 (born in 1921) and who were registered with a participating National Health Service (NHS) general practice in the areas of Newcastle upon Tyne or North Tyneside in the north-east of England. Older persons living in care homes and with disabilities and/or cognitive impairment were included. At baseline (2006/2007), participants underwent a detailed multidimensional health assessment by trained research nurses in their residence (own home or institution), containing questionnaires, measurements, function tests, a fasting blood sample, and a review of medical records held by the general practice [20, 21]. Participants were followed up for an assessment of health and functioning (including self-reported physical activity) at 18 months (1.5 years; wave 2), 36 (3 years; wave 3), and 60 months (5 years; wave 4) by research nurses at their usual place of residence [22, 23]. For the present analysis, data were available for wave 2 and wave 3. The study was approved by the Newcastle and North Tyneside local research ethics committee (06/Q0905/2). Written informed consent was obtained from all participants, otherwise from a caregiver or a relative for those with cognitive impairments [20].

The Tokyo Oldest Old Survey on Total Health (TOOTH) recruited a random sample of community-dwelling seniors aged 85 years or older in the city of Tokyo, Japan. The baseline comprehensive assessment consisted of an in-home interview, a self-administered questionnaire, and a medical/dental examination. Participants were invited to Keio University Hospital for biomedical assessments. For those who were unable to visit the study centre, home-based examinations were done through visits by a geriatrician and a dentist. Socio-demographic characteristics and diseases at baseline were collected. However, since not all determinants were collected in the first year in TOOTH, we defined 3-year follow-up as baseline data, and 6-year follow-up as follow-up variable. The study was approved by the ethical committee of the Keio University School of Medicine (N0. 20,070,047, Dec2007) [24]. Written informed consent was obtained either from the participants or by their proxy (normally a family member or caregiver) if necessary.

A flow chart of recruitment and schematic representation of data samples in the five cohorts is shown in Supplementary Figure 1.

First, each cohort was analysed cross-sectionally to investigate the association of single and a combination of determinants with the presence of anaemia. Then, the studies were analysed prospectively to investigate the effects of the single and the combination of the determinants on the development of incident anaemia. After analysing the studies separately, the data were pooled in a meta-analysis. We further explored the effects of using a cut-off of ferritin of 50 μg/L for iron deficiency, and a combination of significant single determinants as a sensitivity analysis.

Multivariate logistic regression analyses were used to calculate odds ratios (OR) and their 95% confidence intervals. We applied three models: model 1) unadjusted model; model 2) adjusted for socio-demographic characteristics (age, sex, institutionalisation) and smoking; and model 3) a fully adjusted model which included socio-demographic characteristics, smoking and multi-morbidity.

Prospective analyses were done in three studies for which follow-up data were available: the Leiden 85-plus Study, the Newcastle 85+ study and TOOTH. Participants with anaemia at baseline were excluded for the prospective analyses. Multivariate Cox Proportional-Hazards Models were performed, with adjustments for the aforementioned confounding variables.

After acquiring the individual cross-sectional results of the five cohorts and prospective results of the three studies, they were pooled using a two-stage individual participant data (IPD) meta-analysis [34]. Because of the clinical heterogeneity between the studies, random-effects models were applied.

The statistical analyses were performed with SPSS software (version 25) and Review Manager (RevMan). Version 5.3. Copenhagen: The Nordic Cochrane Centre, The Cochrane Collaboration, 2014. for meta-analyses.

Supplementary Table 3 shows the prevalence of anaemia at baseline, depending on the presence of single and a combination of determinants.

Detailed results of unadjusted models and the two models with adjustments for confounders are displayed in Fig. 1 and Supplementary Table 4. After pooling the fully adjusted results of the five cohorts, the pooled adjusted OR for the presence of anaemia for participants with iron deficiency compared to their counterparts without iron deficiency was 2.76 (95% CI, 1.87 to 4.07, I² = 24%). There was no evidence of an association between either vitamin B12 deficiency or folate deficiency and the presence of anaemia. Low eGFR and high CRP were associated with the presence of anaemia.

The prevalence of 0, 1, 2, 3, 4 and 5 determinants for participants with and without anaemia are shown in Supplementary Table 5. Overall, between 17.8 and 56.9% of the participants with anaemia had a sumscore of 0. Per additional determinant the risk of the presence of anaemia was 2.10 (95% CI, 1.85 to 2.38, I² = 0%, P trend< 0.001) (Figs. 1, 2). In addition, a combination of two or more abnormal determinants was significantly associated with the presence of anaemia in all the five cohorts, with a pooled adjusted OR of 3.44 (95% CI, 2.70 to 4.38, I² = 0%; Fig. 1).

Supplementary Table 6 shows the incidence of anaemia at baseline, depending on the presence of single and a combination of determinants.

In the pooled analyses, participants with iron deficiency (Table 2), vitamin B12 deficiency, or folate deficiency (Table 2) did not have a higher risk of developing anaemia during follow-up. Low eGFR was associated with the onset of anaemia (pooled adjusted HR 1.62 95% CI, 1.04 to 2.54, I² = 35%; Table 2). In addition, the pooled estimate of high CRP on the onset of anaemia was 1.40 (95% CI, 1.04 to 1.89, I² = 0%; Table 2).

Per additional determinant the risk of developing anaemia was statistically significant in the Leiden 85-plus Study (HR 1.35 (95% CI, 1.06 to 1.73) and the Newcastle 85+ study (HR 1.58 (95% CI, 1.25 to 1.98) (Table 2), but not for TOOTH. The pooled estimate of the effect on the development of anaemia was 1.46 (95% CI, 1.24 to 1.71, I² = 0%, P trend< 0.001) per additional determinant (Table 2, Fig. 3).

Participants with a combination of ≥2 determinants had a statistically significant 1.87-fold higher risk of developing anaemia compared to those with 0 or 1 determinant (95% CI, 1.12 to 3.12) in the Leiden 85-plus Study and Newcastle 85+ study (HR (95% CI), 2.02 (1.30 to 3.13)), but not in TOOTH. The pooled effect estimate for the onset of anaemia was 1.95 (95% CI, 1.40 to 2.7165, I² = 0%; Table 2, Supplementary Table 7).

Similar results were obtained when a cut-off of 50 μg/L was used to define iron deficiency (Supplementary Tables 8, 9, 10, 11 and 12).

We further explored the effects of a combination of single determinants (iron deficiency, low eGFR and high CRP) that were individually associated with the presence or onset of anaemia, as a sensitivity analysis.

In the cross-sectional analyses, the pooled estimate for the OR on the presence of anaemia was 2.64 (95% CI, 2.22 to 3.14, I² = 15%) per additional determinant. In addition, compared to participants with 0 or 1 determinant, the pooled adjusted OR for a combination of ≥2 of the three significant determinants (iron deficiency, low eGFR and high CRP) on the presence of anaemia was 4.53 (95% CI, 2.66 to 7.72, I² = 50%).

In the prospective analyses, per additional determinant, the risk of development of anaemia increased 1.54 fold (pooled adjusted HR (95% CI), 1.54 (1.24 to 1.92), I² = 11%). In addition, participants with a combination of ≥2 significant determinants had a 1.99-fold higher risk of developing anaemia compared to those with 0 or 1 determinant (pooled adjusted HR 1.99 95% CI, 1.32 to 3.02, I² = 0%).

In this study, we found that very old adults with iron deficiency, low eGFR and high CRP at baseline had a higher risk of having anaemia. A combination of two or more determinants at baseline was associated with the presence of anaemia. Moreover, low eGFR, high CRP and a combination of two and above determinants were associated with the development of anaemia during follow-up.

This study confirmed the well-known association of iron deficiency and the presence of anaemia [35]. Surprisingly, iron deficiency was not associated with anaemia prospectively [36, 37]. Comparable with previous studies in other settings, low eGFR and high CRP were also associated with both the presence and the development of anaemia in this study [38‐40].

We found an increased risk of folate deficiency on anaemia in the Leiden 85-plus Study that corresponded to the previous conclusion in 2008 [27]. However, in the pooled analysis in the TULIPS Consortium, we found no evidence that vitamin B12 and folate deficiency were associated with the presence or onset of anaemia. This is in line with earlier systematic reviews and meta-analyses showing no effect of treatment with vitamin B12 or folic acid on haematological parameters in older individuals [28].

The prevalence of anaemia in TOOTH was almost double that of the other four cohorts but the percentages of single determinants were half. This is in accordance to previous research stating that the frequency of anaemia in Japan is particularly high compared to other countries; moreover, other causes of anaemia such as myelodysplastic syndromes in Japan may be an important determinant for future studies [41].

First, having access to original datasets enabled us to conduct an individual participant data (IPD) meta-analysis to standardize definitions and analyses. In addition, the two-stage method allowed us present the individual study data and to explicitly show the differences in cohorts, and apply well-described standard meta-analysis methods [34]. Second, in the TULIPS Consortium, five cohorts in the very old population were combined which resulted in a large number of very old participants from across the world. This means our results can be extrapolated to a large and diverse group of older individuals worldwide.

We recognize several limitations in our study. First, no full diagnostic work-up for anaemia was performed. Still, our primary analyses are based on measurements of iron status, vitamin B12, folate, CRP and creatinine, which are direct measures or surrogates for the most commonly mentioned causes of anaemia in older persons [1]. These measures are also used in clinical practice to further investigate the cause of anaemia. In addition, we incorporated major clinical conditions such as cardiovascular disease and cancer as important indicators of clinical status, which we accounted for in the analyses. Second, information on serum iron, iron saturation, MCV or other blood counts were not available in all studies. Third, we adjusted for a limited number of comorbidities (cardiovascular disease, cancer and diabetes), as information on other comorbidities was not present in all studies. Residual confounding by e.g. liver disease or gastro-intestinal bleeding may have led to an overestimation of the true associations. Fourth different methods and analysers were applied for the laboratory measurements in the five cohorts. However, the laboratory methods were consistent within each study and were analysed on a study level, which was likely not to have resulted in systematic error, making the effect of differences in laboratory measurements a minor concern. Fifth, small numbers in some subgroups led to inestimable results which could not be pooled in the meta-analyses.

In addition, participants with missing data on single determinants were assumed to be within normal range which could have also led to an underestimation of the current results [42]. Last, the determinants were measured once at baseline. Patients who had transient deficiency, who developed abnormality over time, or who reverted to normal levels probably due to supplement use during follow-up may have been misclassified.