Evidence map›Paper›PMID 33765116›Full record

ArticleAge and ageing2021

Individual changes in anthropometric measures after age 60 years: a 15-year longitudinal population-based study.

Jie Guo, Ying Shang, Laura Fratiglioni, Kristina Johnell, Anna-Karin Welmer, Anna Marseglia, Weili Xu

Open access · greenAbstract read
In one paragraph

Article in Age and ageing, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
2.4field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Observational
  5. Article
  6. Associations Between Mid- to Late-Life Body Mass Index and Chronic Disease-Free Survival: A Nationwide Twin Study.The journals of gerontology. Series A, Biological sciences and medical sciences · 2024
    Article
  7. Article
  8. Observational
  9. Article
  10. Article
  11. Article
  12. Article
  13. Overweight in Older Adults: A Follow-Up of Fifteen Years of the SABE Survey.International journal of environmental research and public health · 2023
    Article
  14. Association Between Late-Life Weight Change and Dementia: A Population-based Cohort Study.The journals of gerontology. Series A, Biological sciences and medical sciences · 2023
    Article
  15. Article
  16. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Jie GuoAging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.ORCID 0000-0001-6104-9957
Ying ShangAging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
Laura FratiglioniAging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
Kristina JohnellDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Anna-Karin WelmerAging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
Anna MarsegliaAging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
Weili XuAging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
Stockholm University · SEKarolinska Institutet · SEKarolinska University Hospital · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundweight loss is commonly observed with ageing. We explored the trajectory of body mass index (BMI) and two proxies of muscle mass-calf circumference (CC) and mid-arm circumference (MAC)-and identified their determinants.

methodswithin the SNAC-K cohort, 2,155 dementia-free participants aged ≥60 years were followed over 15 years. BMI, CC and MAC were measured at baseline and follow-ups. Baseline sociodemographic and lifestyle factors were collected through interviews. Diabetes and vascular disorders were diagnosed by physicians through clinical examination and medical records. Data were analysed using linear mixed-effect models stratified by age (younger-old [<78 years] vs. older-old [≥78 years]).

resultsover the 15-year follow-up, BMI remained stable among participants aged 60 years at baseline (βslope = 0.009 [95% confidence interval -0.006 to 0.024], P = 0.234) and declined significantly among those aged ≥66 years, while CC and MAC declined significantly across all age groups. The decline over 15 years in BMI, CC and MAC separately was 0.435 kg/m2, 1.110 cm and 1.455 cm in the younger-old and was 3.480 kg/m2, 3.405 cm and 3.390 cm in the older-old. In younger-old adults, higher education was associated with slower declines in all three measures, while vascular disorders and diabetes were associated with faster declines. In older-old adults, vigorous physical activity slowed declines in BMI and CC, while vascular disorders accelerated declines in BMI and MAC.

conclusionsCC and MAC declined earlier and more steeply than BMI. Cardiometabolic disorders accelerated such declines, while higher education and physical activity could counteract those declines.

Indexed as

AgingLegAgedBody Mass IndexCohort StudiesHumansLongitudinal StudiesWeight Lossageingbody mass indexcalf circumferencemid-arm circumferenceolder peopletrajectories

Identifiers

PMID33765116
PMCPMC8437063
OpenAlexW3136382470

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.