Evidence map›Paper›PMID 31728387›Full record

ArticleInternational journal of nursing sciences2019

Nurse staffing and life expectancy at birth and at 65 years old: Evidence from 35 OECD countries.

Arshia Amiri, Tytti Solankallio-Vahteri

Abstract read
In one paragraph

Article in International journal of nursing sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. 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

2 authors.

Arshia AmiriJAMK University of Applied Sciences, Jyväskylä, Finland.
Tytti Solankallio-VahteriJAMK University of Applied Sciences, Jyväskylä, Finland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo measure the possible magnitude of the role nurse staffing has on increasing life expectancy at birth and at 65 years old.

methodsThe statistical technique of panel data analysis was applied to investigate the relationship from the number of practicing nurses' density per 1000 population to life expectancy at birth and at 65 years old. Five control variables were used as the proxies for the levels of medical staffing, health care financial and physical resources, and medical technology. The observations of 35 member countries of Organization for Economic Co-operation and Development (OECD) were collected from OECD Health Statistics over 2000-2016 period.

resultsThere were meaningful relationships from nurse staffing to life expectancy at birth and at 65 years with the long-run elasticities of 0.02 and 0.08, respectively. Overall, the role of nursing characteristics in increasing life expectancy indicators varied among different health care systems of OECD countries and in average were determined at the highest level in Japan (0.25), followed by Iceland (0.24), Belgium (0.21), Czech Republic (0.21), Slovenia (0.20) and Sweden (0.18).

conclusionA higher proportion of nursing staff is associated with higher life expectancy in OECD countries and the dependency of life expectancy to nursing staff would increase by aging. Hence, the findings of this study warn health policy makers about ignoring the effects nursing shortages create e.g. increasing the risk of actual age-specific mortality, especially in care of elderly people.

Indexed as

Health manpowerLife expectancyNursing servicesNursing staffOrganization for Economic Co-Operation and DevelopmentPanel data analysisQuality of health care

Identifiers

PMID31728387
PMCPMC6838842

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.