HUMANITYVECTOR

Relationship, affects

Economic output affects Human health and longevity

The stored status is what a reviewer approved. The level below it is what the overlapping data support; the two are shown side by side and only a human moves the status.

Stored statusMechanism supportedEvidence level (latest analysis)Level 3: Mechanism supported

Mechanism, evidence, reviewer judgements

The edge as stored

Economic output affects Human health and longevity4 evidenceMechanism supported

Human health and longevity depends on Economic output.

Mechanism

Higher output per person funds nutrition, sanitation, clinics, vaccines and education, and the relation between income and life expectancy across countries and time (the Preston curve) is one of the most documented in demography. The curve shifts upward over time, so part of the gain in longevity comes from knowledge and public health rather than income, and the effect flattens at high income.

Evidence

Status
mechanism_supported
Reviewer confidence
0.80
Stated strength
0.50
Lag
365 to 3650 days
Version
curated_seed_v1
Reviewed
2026-09-07

Confidence and strength are curated judgements recorded with the edge, not measured quantities.

Entity pages: Economic output, Human health and longevity.

Level 3 evidence, computed 2026-09-07 22:15 UTC

Correlation

DerivedLevel 3: Mechanism supported

GDP per person, constant 2015 US$ against Life expectancy at birth, geography WLD, 65 overlapping years (1960 to 2024). Primary statistics on diff (first differences, because at least one series has a unit root; levels are shown for comparison).

Pearson r (diff)

0.031

p 0.8088

Spearman rho (diff)

-0.001

p 0.9908

Pearson r (levels)

0.965

two trending series correlate in levels by construction

Rolling r

0.179

min -0.627, max 0.971, 5 sign changes

GDP per person, constant 2015 US$ and Life expectancy at birth, each scaled to its own range over 1960 to 2024Aligned series, scaled 0 to 1 over the overlap00.51GDP per person, constant 2015 US$, 1960: 3666.591GDP per person, constant 2015 US$, 1961: 3758.773GDP per person, constant 2015 US$, 1962: 3889.442GDP per person, constant 2015 US$, 1963: 3999.117GDP per person, constant 2015 US$, 1964: 4176.129GDP per person, constant 2015 US$, 1965: 4321.264GDP per person, constant 2015 US$, 1966: 4461.252GDP per person, constant 2015 US$, 1967: 4534.504GDP per person, constant 2015 US$, 1968: 4706.692GDP per person, constant 2015 US$, 1969: 4884.728GDP per person, constant 2015 US$, 1970: 4964.267GDP per person, constant 2015 US$, 1971: 5060.962GDP per person, constant 2015 US$, 1972: 5235.595GDP per person, constant 2015 US$, 1973: 5464.502GDP per person, constant 2015 US$, 1974: 5466.805GDP per person, constant 2015 US$, 1975: 5409.878GDP per person, constant 2015 US$, 1976: 5590.919GDP per person, constant 2015 US$, 1977: 5710.217GDP per person, constant 2015 US$, 1978: 5843.072GDP per person, constant 2015 US$, 1979: 5978.088GDP per person, constant 2015 US$, 1980: 5980.250GDP per person, constant 2015 US$, 1981: 5986.165GDP per person, constant 2015 US$, 1982: 5902.836GDP per person, constant 2015 US$, 1983: 5947.172GDP per person, constant 2015 US$, 1984: 6119.787GDP per person, constant 2015 US$, 1985: 6233.016GDP per person, constant 2015 US$, 1986: 6325.607GDP per person, constant 2015 US$, 1987: 6446.303GDP per person, constant 2015 US$, 1988: 6619.581GDP per person, constant 2015 US$, 1989: 6741.216GDP per person, constant 2015 US$, 1990: 6804.126GDP per person, constant 2015 US$, 1991: 6773.416GDP per person, constant 2015 US$, 1992: 6801.305GDP per person, constant 2015 US$, 1993: 6818.570GDP per person, constant 2015 US$, 1994: 6944.091GDP per person, constant 2015 US$, 1995: 7057.773GDP per person, constant 2015 US$, 1996: 7202.740GDP per person, constant 2015 US$, 1997: 7381.771GDP per person, constant 2015 US$, 1998: 7478.784GDP per person, constant 2015 US$, 1999: 7638.929GDP per person, constant 2015 US$, 2000: 7879.618GDP per person, constant 2015 US$, 2001: 7932.442GDP per person, constant 2015 US$, 2002: 8010.647GDP per person, constant 2015 US$, 2003: 8151.037GDP per person, constant 2015 US$, 2004: 8408.565GDP per person, constant 2015 US$, 2005: 8639.359GDP per person, constant 2015 US$, 2006: 8913.157GDP per person, constant 2015 US$, 2007: 9191.474GDP per person, constant 2015 US$, 2008: 9265.527GDP per person, constant 2015 US$, 2009: 9028.221GDP per person, constant 2015 US$, 2010: 9322.218GDP per person, constant 2015 US$, 2011: 9514.520GDP per person, constant 2015 US$, 2012: 9653.627GDP per person, constant 2015 US$, 2013: 9811.026GDP per person, constant 2015 US$, 2014: 10000.583GDP per person, constant 2015 US$, 2015: 10191.975GDP per person, constant 2015 US$, 2016: 10355.045GDP per person, constant 2015 US$, 2017: 10591.555GDP per person, constant 2015 US$, 2018: 10822.575GDP per person, constant 2015 US$, 2019: 10996.910GDP per person, constant 2015 US$, 2020: 10575.219GDP per person, constant 2015 US$, 2021: 11167.604GDP per person, constant 2015 US$, 2022: 11452.020GDP per person, constant 2015 US$, 2023: 11670.822GDP per person, constant 2015 US$, 2024: 11894.252Life expectancy at birth, 1960: 50.942Life expectancy at birth, 1961: 52.797Life expectancy at birth, 1962: 55.286Life expectancy at birth, 1963: 55.652Life expectancy at birth, 1964: 56.097Life expectancy at birth, 1965: 55.927Life expectancy at birth, 1966: 56.449Life expectancy at birth, 1967: 56.904Life expectancy at birth, 1968: 57.336Life expectancy at birth, 1969: 57.680Life expectancy at birth, 1970: 57.937Life expectancy at birth, 1971: 58.025Life expectancy at birth, 1972: 58.844Life expectancy at birth, 1973: 59.296Life expectancy at birth, 1974: 59.700Life expectancy at birth, 1975: 60.131Life expectancy at birth, 1976: 60.454Life expectancy at birth, 1977: 61.041Life expectancy at birth, 1978: 61.394Life expectancy at birth, 1979: 61.841Life expectancy at birth, 1980: 62.152Life expectancy at birth, 1981: 62.517Life expectancy at birth, 1982: 62.874Life expectancy at birth, 1983: 63.132Life expectancy at birth, 1984: 63.436Life expectancy at birth, 1985: 63.725Life expectancy at birth, 1986: 64.116Life expectancy at birth, 1987: 64.458Life expectancy at birth, 1988: 64.666Life expectancy at birth, 1989: 64.958Life expectancy at birth, 1990: 65.109Life expectancy at birth, 1991: 65.304Life expectancy at birth, 1992: 65.548Life expectancy at birth, 1993: 65.743Life expectancy at birth, 1994: 65.959Life expectancy at birth, 1995: 66.201Life expectancy at birth, 1996: 66.515Life expectancy at birth, 1997: 66.831Life expectancy at birth, 1998: 67.067Life expectancy at birth, 1999: 67.312Life expectancy at birth, 2000: 67.650Life expectancy at birth, 2001: 67.945Life expectancy at birth, 2002: 68.231Life expectancy at birth, 2003: 68.516Life expectancy at birth, 2004: 68.771Life expectancy at birth, 2005: 69.111Life expectancy at birth, 2006: 69.469Life expectancy at birth, 2007: 69.805Life expectancy at birth, 2008: 70.004Life expectancy at birth, 2009: 70.380Life expectancy at birth, 2010: 70.683Life expectancy at birth, 2011: 70.969Life expectancy at birth, 2012: 71.265Life expectancy at birth, 2013: 71.533Life expectancy at birth, 2014: 71.776Life expectancy at birth, 2015: 71.966Life expectancy at birth, 2016: 72.186Life expectancy at birth, 2017: 72.366Life expectancy at birth, 2018: 72.644Life expectancy at birth, 2019: 72.870Life expectancy at birth, 2020: 72.183Life expectancy at birth, 2021: 71.216Life expectancy at birth, 2022: 72.969Life expectancy at birth, 2023: 73.330Life expectancy at birth, 2024: 73.482GDP per person, constant 2015 US$Life expectancy at birthRolling correlation, window 10 (on the primary transform)-101rolling r ending 1970: -0.19rolling r ending 1971: 0.04rolling r ending 1972: 0.30rolling r ending 1973: 0.32rolling r ending 1974: 0.18rolling r ending 1975: 0.25rolling r ending 1976: 0.18rolling r ending 1977: 0.19rolling r ending 1978: 0.18rolling r ending 1979: 0.22rolling r ending 1980: 0.25rolling r ending 1981: 0.35rolling r ending 1982: 0.25rolling r ending 1983: 0.16rolling r ending 1984: 0.05rolling r ending 1985: 0.13rolling r ending 1986: 0.21rolling r ending 1987: 0.07rolling r ending 1988: -0.20rolling r ending 1989: -0.47rolling r ending 1990: -0.30rolling r ending 1991: -0.00rolling r ending 1992: 0.38rolling r ending 1993: 0.45rolling r ending 1994: 0.35rolling r ending 1995: 0.32rolling r ending 1996: 0.47rolling r ending 1997: 0.57rolling r ending 1998: 0.71rolling r ending 1999: 0.67rolling r ending 2000: 0.82rolling r ending 2001: 0.66rolling r ending 2002: 0.61rolling r ending 2003: 0.45rolling r ending 2004: 0.24rolling r ending 2005: 0.32rolling r ending 2006: 0.50rolling r ending 2007: 0.56rolling r ending 2008: 0.60rolling r ending 2009: -0.07rolling r ending 2010: -0.12rolling r ending 2011: -0.14rolling r ending 2012: -0.16rolling r ending 2013: -0.16rolling r ending 2014: -0.13rolling r ending 2015: -0.19rolling r ending 2016: -0.34rolling r ending 2017: -0.56rolling r ending 2018: -0.63rolling r ending 2019: 0.09rolling r ending 2020: 0.97rolling r ending 2021: 0.02rolling r ending 2022: 0.14rolling r ending 2023: 0.14rolling r ending 2024: 0.1419601976199220082024
  • no significant association on diff (n 65)
  • Granger-style test significant in one direction only (x to y)
  • stored status carries a documented mechanism with cited evidence (floor at 3)

Cross-correlation scan and Granger-style tests

Lead and lag

Cross-correlation by lag between GDP per person, constant 2015 US$ and Life expectancy at birth; positive lag means GDP per person, constant 2015 US$ leadsCross-correlation by lag (positive lag: GDP per person, constant 201 leads)-1-0.500.51lag -5: r -0.05 (n 59)-5lag -4: r -0.03 (n 60)-4lag -3: r -0.07 (n 61)-3lag -2: r -0.06 (n 62)-2lag -1: r -0.13 (n 63)-1lag 0: r 0.03 (n 64)0lag 1: r 0.36 (n 63)+1lag 2: r -0.41 (n 62), strongest+2lag 3: r -0.12 (n 61)+3lag 4: r 0.03 (n 60)+4lag 5: r 0.01 (n 59)+5lag in periods; strongest at +2 (r -0.41), same period r 0.03
DirectionTestedlag 1 plag 2 plag 3 plag 4 plag 5 pmin pReading
GDP per person, constant 2015 US$ helps predict Life expectancy at birthyes0.0030.0000.0000.0000.0000.0000predictive at lag 2 (p < 0.05)
Life expectancy at birth helps predict GDP per person, constant 2015 US$yes0.3120.6750.5390.4690.1970.1969no predictive information beyond own past

Granger-style F-tests on the primary transform: whether lagged values of one series improve a regression of the other on its own lags. Predictive information is not causation; a common driver that moves one series earlier produces the same pattern.

Reading: GDP per person, constant 2015 US$ historically leads Life expectancy at birth.

Cointegration
no (p 0.929)
Changepoints
GDP per person, co: 1, Life expectancy at: 1
ADF p (levels)
0.999, 0.077
Service
causal-service/0.1.0

Computed 2026-09-07 22:15 UTC

Causal estimate

ModeledLevel 3: Mechanism supported

Treatment GDP per person, constant 2015 US$ (economic-output), outcome Life expectancy at birth (human-health), controls Population with access to electricity, Gross capital formation as share of GDP, Renewable freshwater resources per person. Method backdoor.linear_regression on diff, n 25.

Estimate (outcome units per treatment unit)

0.0007

95 percent CI

-0.0008 to 0.0023

includes zero

Refutations

3 of 3 passed

RefutationEffect afterpResultExpectation
placebo treatment-0.00000.485passedplacebo treatment (permuted) should produce an effect near zero
random common cause0.00070.431passedestimate should not move materially (p is the probability the change is noise)
data subset0.00050.457passedestimate should not move materially (p is the probability the change is noise)

Assumptions

  1. Backdoor adjustment: conditioning on electricity-access, gross-capital-formation-share, renewable-freshwater-per-person closes every non-causal path between gdp-per-person and life-expectancy. Unmeasured common causes would bias the estimate.
  2. Linear, additive effect of the treatment on the outcome across the overlapping periods; no heterogeneous or threshold effects.
  3. Series are first-differenced (a unit-root test rejected stationarity for at least one series); the estimate is a same-period association after adjustment, not a dynamic response.
  4. The direction of the arrow (treatment to outcome) comes from the stored relationship and its mechanism, not from the data.
  5. No reverse causation and no selection into the sample of periods.

Alternative explanations

  • Reverse causation: the outcome may drive the treatment.
  • An omitted common cause not in the controls moves both series.
  • Shared trend or regime: both series respond to the same global shock.
  • Aggregation: world-level annual data hides country-level variation and timing.
  • Measurement and revision: both series are estimates that are revised over time.
Identified estimand (DoWhy)
Estimand type: nonparametric-ate

### Estimand : 1
Estimand name: backdoor
Estimand expression:
        d                                                                      ↪
─────────────────(E[life-expectancy|gross-capital-formation-share,electricity- ↪
d[gdp-per-person]                                                              ↪

↪                                         
↪ access,renewable-freshwater-per-person])
↪                                         
Estimand assumption 1, Unconfoundedness: If U→{gdp-per-person} and U→life-expectancy then P(life-expectancy|gdp-per-person,gross-capital-formation-share,electricity-access,renewable-freshwater-per-person,U) = P(life-expectancy|gdp-per-person,gross-capital-formation-share,electricity-access,renewable-freshwater-per-person)

### Estimand : 2
Estimand name: iv
No such variable(s) found!

### Estimand : 3
Estimand name: frontdoor
No such variable(s) found!
  • no significant association on diff (n 65)
  • Granger-style test significant in one direction only (x to y)
  • stored status carries a documented mechanism with cited evidence (floor at 3)
  • backdoor estimate: CI includes zero

Alternative explanations for the association

What else could explain it

  • Both series trend with world development; the primary statistics use first differences to limit that, not remove it.
  • A common driver (income, urbanisation, technology) can move both series with different lags and produce a lead/lag pattern without any direct effect.
  • World aggregates hide country composition: a change in which countries report can move a world series.
  • Reverse direction: Human health and longevity may act on Economic output.
  • Both series are revised by their source; the analysis uses the current vintage, not the vintage available at the time.

What each rung means

Levels

  1. Level 0: No association found

    the overlapping data show no significant association.

  2. Level 1: Correlation only

    statistically associated in the overlapping periods; no direction, no mechanism.

  3. Level 2: Predictive lead/lag

    one series historically contains predictive information about the other.

  4. Level 3: Mechanism supported

    a documented physical, economic or institutional mechanism with cited evidence.

  5. Level 4: Causally supported

    a backdoor-adjusted estimate that survived refutation, on stated assumptions.

  6. Level 5: Established relation

    follows from engineering, accounting or scientific structure.

Every stored run, newest first

Analysis history

  • 2026-09-07 22:15 causal level 3 n 65 causal-service/0.1.0
  • 2026-09-07 22:15 correlate level 3 n 65 causal-service/0.1.0