Early-Life Conditions, Rapid Demographic Changes, and Older Adult Health in the Developing World

Figures & data

Table 1 General framework for the nature of mortality decline across countries in the early to mid-twentieth century and expected health patterns in older adults

Country type A		Country type E
Nature of mortality decline at birth
Early graded	Mortality decline	Late, rapid
Higher fraction	Improvements in SES	Lower fraction
Smaller fraction	Public health interventions	Higher fraction
Expected health patterns in older adults
Less	Poor health	Greater
Weaker	Early life conditions	Stronger
Weaker	SES differentials	Stronger
Lower	Expected mortality risk	Higher

Source: Adapted from McEniry (2014).

Notes: Country type A includes developed countries (e.g., England, The Netherlands, the United States), and country type E includes low-income countries (e.g., China, Ghana, India, Indonesia). In between these extremes are predominantly middle-income countries (types B–D: Costa Rica, Mexico, South Africa), characterized by differences in the timing, pace, and reason for mortality decline during the 1930s–1960s.

Table 2 Sample characteristics for cross-national data on aging populations born during the late 1920s–early 1940s in selected countries

	Middle-income countries			Low-income countries
Variables/countries	Costa Rica	South Africa	Mexico	China	Ghana	India	Indonesia
Age	68 (5.3)	69 (6.0)	72 (5.7)	70 (5.4)	70 (5.5)	69 (5.1)	62 (5.0)
Female (%)	52	62	50	53	49	48	55
Childhood
Born rural (%)	72	43	32	54	61	72	84
Father no education (%)		58	58	74	87	68	67
Years schooling	5.2 (4.1)	4.9 (4.7)	4.1 (4.2)	4.7 (4.7)	3.3 (5.0)	3.2 (4.4)	3.4 (3.9)
Height (avg, in cm)
Female	150.7	154.4	148.8	152.5	156.6	148.4	147.3
Male	164.4	159.1	163.7	163.0	164.8	162.5	158.6
Adulthood
Obese (%)	25	48	26	6	8	2	2
Diabetes (%)	22	11	20	9	4	7	4
Hypertension (%)	72	82	75	69	60	38	63
Visited doctor (%)	93	69	42	60	68	88	9
Rural residence (%)	38	39	27	45	60	70	62
Never smoked (%)	58	69	57	67	74	43	51
Smoked but not now (%)	32	10	23	9	15	6	6
Current smoker (%)	11	22	20	25	11	51	43

Source: RELATE (2013), weighted, low- and middle-income countries where both measured blood pressure and variables on childhood conditions were available; harmonized variables where applicable; older adults born during the late 1920s through early 1940s.

Notes: The table is based on a total sample of 16,836 respondents. Sample sizes for individual countries were: Costa Rica = 1,654; South Africa = 1,475; Mexico–SAGE = 1,169; China–SAGE = 5,363; Ghana = 1,946; India = 2,723; and Indonesia = 2,506. All numbers are either percentages (where indicated) or averages, with standard deviations in parentheses. Age is at the time of the surveys. SAGE respondents are slightly older than other older adult respondents because of timing of the surveys. The averages appearing for diabetes are age-standardized (Ahmad et al. 2001) and are shown in Figure 3. Hypertension was defined to be a systolic rate of ≥ 140 mmHg, a diastolic rate of ≥ 90 mmHg, or taking medication to control hypertension. Visited doctor indicates if the respondent visited a doctor or similar medical professional at least once during the year before the survey. Rural residence is the percent of respondents who lived in a rural area at the time of the survey.

Table 3 Models predicting obesity

	Model 1		Model 2
	OR	95% CI	OR	95% CI
Age	0.97	[0.96–0.99]	0.97	[0.96–0.98]
Female	1.96	[1.70–2.27]	1.94	[1.68–2.24]
Born rural	0.66	[0.57–0.76]	0.90	[0.74–1.10]
Low height	1.65	[1.45–1.88]	1.65	[1.45–1.89]
Years schooling	1.04	[1.02–1.05]	1.03	[1.02–1.05]
Health utilization	1.21	[1.04–1.40]	1.20	[1.03–1.39]
Rural residence			0.64	[0.52–0.79]
Smoking
Never (ref)	1.00		1.00
Past	0.77	[0.62–0.96]	0.76	[0.61–0.95]
Current	0.52	[0.43–0.62]	0.52	[0.43–0.62]
Country
Middle income
Mexico	5.29	[4.23–6.62]	5.08	[4.06–6.37]
South Africa	8.14	[6.62–10.00]	7.93	[6.45–9.75]
Low income
China	0.66	[0.54–0.82]	0.64	[0.52–0.79]
Ghana (ref)	1.00		1.00
India	0.39	[0.29–0.53]	0.40	[0.29–0.53]

Source: RELATE (2013), older adults born during the late 1920s through the early 1940s; SAGE countries only, n = 12,676.

Figure 1. Predicted probabilities for obesity by country.

Source: Predicted probabilities using Model 2, Table 3; holding model variables at means. Vertical lines show 95% confidence intervals.Notes: There are noted differences in gender (female, male) for India (0.04, 0.02), Ghana (0.09, 0.05), China (0.06, 0.03), South Africa (0.44, 0.29), and Mexico (0.33, 0.20). Similar results obtained for all seven countries (results not shown).

Figure 2. Predicted probabilities of being obese by country, height, and urban residence.

Source: Predicted probabilities using Model 2, Table 3; holding model variables at means; vertical lines show 95% confidence intervals.Notes: Similar results obtained for all seven countries (results not shown). For each country, left bar = Q1, right bar = Q2–Q4.

Figure 3. Predicted probabilities for obesity by country and height.

Source: Predicted probabilities using Model 2, Table 3, using continuous height (cm). Vertical lines show 95% confidence intervals.Notes: Predicted probabilities showing gender by country produced no notable differences.

Table 4 Models predicting diabetes and hypertension

	Diabetes				Hypertension
	Model 1		Model 2		Model 3		Model 4
	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI
Age	1.01	[1.00–1.02]	1.01	[1.00–1.02]	1.03	[1.02–1.03]	1.02	[1.02–1.03]
Female	1.13	[0.98–1.30]	1.10	[0.95–1.27]	1.18	[1.08–1.29]	1.17	[1.07–1.28]
Born rural	0.49	[0.43–0.57]	0.85	[0.70–1.03]	0.88	[0.81–0.96]	0.96	[0.84–1.09]
Low height	0.87	[0.76–1.01]	0.89	[0.77–1.03]	0.93	[0.85–1.01]	0.93	[0.85–1.01]
Years schooling	1.05	[1.04–1.07]	1.05	[1.03–1.06]	1.01	[1.00–1.02]	1.01	[1.00–1.02]
Health utilization	1.64	[1.41–1.91]	1.63	[1.40–1.90]	1.25	[1.13–1.38]	1.25	[1.13–1.38]
Rural residence			0.45	[0.36–0.55]			0.89	[0.78–1.02]
Obesity	1.37	[1.14–1.64]	1.34	[1.12–1.61]	1.56	[1.35–1.81]	1.55	[1.34–1.80]
Smoking
Never (ref)	1.00		1.00		1.00		1.00
Past	0.95	[0.77–1.17]	0.94	[0.76–1.16]	1.06	[0.92–1.22]	1.06	[0.92–1.22]
Current	0.64	[0.54–0.76]	0.65	[0.55–0.77]	0.85	[0.77–0.94]	0.85	[0.77–0.94]
Country
Middle income
Mexico	5.55	[4.24–7.26]	5.20	[3.97–6.81]	1.64	[1.39–1.94]	1.62	[1.37–1.92]
South Africa	2.36	[1.78–3.14]	2.26	[1.71–3.00]	2.54	[2.15–3.01]	2.52	[2.13–2.99]
Low income
China	2.12	[1.67–2.70]	1.96	[1.54–2.49]	1.52	[1.36–1.70]	1.51	[1.35–1.68]
Ghana (ref)	1.00		1.00		1.00		1.00
India	2.44	[1.88–3.18]	2.50	[1.92–3.26]	0.49	[0.43–0.56]	0.49	[0.43–0.56]

Source: RELATE (2013), older adults born during the late 1920s through the early 1940s; SAGE countries only, n = 12,676.

Table A1 Models using all seven countries predicting health outcomes

	Obesity		Diabetes		Hypertension
	OR	95% CI	OR	95% CI	OR	95% CI
Age	0.97	[0.96–0.98]	1.01	[1.00–1.02]	1.03	[1.02–1.04]
Female	1.97	[1.73–2.24]	1.07	[0.95–1.22]	1.21	[1.11–1.30]
Born rural	0.91	[0.79–1.06]	0.78	[0.68–0.90]	0.98	[0.89–1.08]
Low height	1.53	[1.36–1.73]	0.85	[0.75–0.97]	0.93	[0.87–1.00]
Years schooling	1.03	[1.02–1.04]	1.03	[1.02–1.05]	1.00	[1.00–1.01]
Health utilization	1.26	[1.09–1.45]	1.75	[1.51–2.03]	1.22	[1.11–1.34]
Rural residence	0.63	[0.54–0.73]	0.56	[0.48–0.65]	0.87	[0.79–0.96]
Obesity			1.59	[1.37–1.85]	1.61	[1.42–1.84]
Smoking
Never (ref)	1.00		1.00		1.00
Past	0.87	[0.74–1.04]	0.90	[0.77–1.07]	1.02	[0.91–1.15]
Current	0.47	[0.39–0.56]	0.63	[0.54–0.73]	0.84	[0.77–0.91]
Country
Middle income
Costa Rica	3.50	[2.82–4.36]	5.04	[3.90–6.51]	1.69	[1.45–1.96]
Mexico	5.12	[4.09–6.42]	5.31	[4.06–6.94]	1.59	[1.35–1.88]
South Africa	8.12	[6.61–9.97]	2.22	[1.68–2.93]	2.53	[2.14–2.99]
Low income
China	0.65	[0.53–0.80]	2.08	[1.64–2.64]	1.50	[1.35–1.68]
Ghana (ref)	1.00		1.00		1.00
India	0.40	[0.30–0.55]	2.47	[1.90–3.21]	0.50	[0.44–0.56]
Indonesia	0.27	[0.19–0.38]	1.55	[1.10–2.18]	1.77	[1.53–2.04]

Source: RELATE (2013), older adults born during the late 1920s through the early 1940s; all seven selected countries, n = 16,836.

McEniry, M. 2014. Early life conditions and rapid demographic changes in the developing world: Consequences for older adult health. Dordrecht, Netherlands: Springer Science and Business Media.

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