Airflow Obstruction and Cardio-metabolic Comorbidities

Figures & data

Table 1. General characteristics of study participants at each site and overall.

Site, Country	N	Smoking Status (%)			Sex (%)	Age (years)		BMI (kg/m^2)		AO (%)	Comorbidities (%)			GNI
		Current	Ex	Never	Male	Mean ± SD		Mean ± SD			CVD	H	D	High
Adana, Turkey	806	34.9	19.9	45.3	48.3	53.6 ± 10.4		29.6 ± 5.3		14.3	11.8	27.0	10.3	no
Annaba, Algeria	862	16.7	21.9	61.4	49.8	52.9 ± 9.7		28.3 ± 5.7		7.0	6.6	22.2	14.4	no
Bergen, Norway	656	26.2	36.6	37.2	49.2	59.7 ± 12.5		26.5 ± 4.3		12.5	15.4	29.4	5.9	yes
Blantyre, Malawi	399	3.8	9.3	87.0	39.8	52.2 ± 9.7		25.1 ± 5.4		8.3	2.5	20.1	6.0	no
Cape Town, SA	833	46.3	21.4	32.3	37.0	54.0 ± 10.2		27.9 ± 7.4		18.6	13.3	38.9	13.2	no
Chui, Kyrgyztan	858	19.8	9.7	70.5	31.5	53.0 ± 8.8		28.5 ± 5.6		10.0	16.6	29.7	5.7	no
Colombo, Srilanka	1020	12.9	7.5	79.6	44.6	53.7 ± 9.4		24.2 ± 4.6		7.3	5.9	20.6	13.4	no
Cotonou, Benin	677	1.8	0.1	98.1	43.9	51.5 ± 9.3		26.4 ± 5.5		7.7	5.3	29.8	2.5	no
Fes, Morocco	758	8.6	18.7	72.7	46.0	55.2 ± 10.0		27.9 ± 5.3		9.6	5.8	33.1	14.6	no
Guangzhou, China	471	29.9	14.0	56.1	49.9	54.0 ± 10.6		23.3 ± 3.3		7.9	9.8	17.6	4.0	no
Hannover, Germany	681	20.7	39.4	39.9	51.2	58.0 ± 10.9		27.3 ± 4.6		8.8	17.0	38.3	6.3	yes
Ife, Nigeria	859	2.6	7.9	89.5	39.1	55.5 ± 11.5		25.4 ± 5.4		6.9	0.2	2.3	0.8	no
Krakow, Poland	522	29.3	32.4	38.3	50.8	55.6 ± 11.4		27.7 ± 4.7		13.6	32.4	42.0	11.1	yes
Lexington, USA	505	26.5	33.9	39.6	40.4	56.5 ± 9.8		30.8 ± 6.8		15.0	29.3	49.1	17.4	yes
Lisbon, Portugal	709	13.3	26.8	59.9	46.7	63.3 ± 11.3		28.2 ± 4.7		11.6	17.5	37.5	11.0	yes
London, England	672	21.0	41.2	37.8	48.1	58.0 ± 11.4		27.1 ± 5.0		15.8	7.1	33.0	6.5	yes
Maastricht, NL	589	22.9	42.4	34.6	50.8	57.5 ± 10.6		27.4 ± 4.5		18.2	17.0	29.5	7.3	yes
Manila, Philippines	890	32.7	20.2	47.1	42.2	52.2 ± 10.1		24.9 ± 4.7		8.5	11.0	26.5	6.0	no
Mumbai, India	440	6.6	3.2	90.2	62.5	51.1 ± 8.9		23.8 ± 4.0		6.8	2.3	10.0	5.2	no
NT, Philippines	722	35.9	16.8	47.4	49.3	54.1 ± 10.5		21.5 ± 3.9		14.3	8.3	19.7	2.6	no
Naryn, Kyrgyztan	816	15.1	9.8	75.1	38.5	53.2 ± 9.7		27.0 ± 5.0		7.4	11.6	15.7	1.0	no
Penang, Malaysia	646	20.3	5.0	74.8	50.9	54.8 ± 9.3		26.0 ± 4.5		4.0	2.8	25.2	14.4	no
Pune, India	843	8.9	3.0	88.1	59.4	52.4 ± 9.8		22.1 ± 3.8		6.2	1.4	5.1	2.1	no
Reykjavik, Iceland	755	18.4	42.5	39.1	53.1	56.3 ± 11.6		27.9 ± 4.9		11.0	15.4	32.1	4.8	yes
Riyadh, Saudi Arabia	654	7.8	17.0	75.2	54.9	50.5 ± 7.5		31.2 ± 6.0		3.1	6.7	26.6	29.4	no
Salzburg, Austria	1255	19.3	33.5	47.2	54.3	57.6 ± 11.3		26.4 ± 4.2		15.8	12.5	28.9	6.4	yes
Sousse, Tunisia	658	26.7	13.2	60.0	47.0	53.0 ± 9.0		29.3 ± 5.6		5.0	5.6	21.0	10.9	no
Srinagar, India	739	10.3	1.9	87.8	54.9	51.7 ± 10.3		22.4 ± 3.6		16.4	1.4	27.1	2.2	no
Sydney, Australia	423	14.9	36.6	48.5	49.6	58.5 ± 11.9		28.0 ± 5.1		10.2	12.8	29.8	8.5	yes
Tartu, Estonia	611	18.2	29.3	52.5	50.2	60.8 ± 12.0		28.4 ± 5.2		7.0	37.3	40.1	7.2	yes
Tirana, Albania	926	21.8	15.2	63.0	49.8	54.7 ± 10.6		28.1 ± 4.7		8.6	4.2	22.8	6.5	no
Uppsala, Sweden	547	14.3	43.1	42.6	51.7	58.4 ± 10.9		27.0 ± 4.4		9.3	11.0	28.7	3.8	yes
Vancouver, Canada	821	13.9	38.4	47.7	41.7	55.8 ± 11.5		26.7 ± 5.2		12.3	12.8	20.2	7.1	yes
Total: n = 23623		19.0	21.1	59.8	47.5	55.1 ± 10.8		26.7 ± 5.5		10.4	10.8	26.2	8.1	37%

Abbreviations: BMI: body mass index. AO: airflow obstruction. GNI: gross national income. CVD: cardiovascular disease. H: hypertension. D: diabetes. SA: South Africa. USA: United States of America. NL: The Netherlands. NT: Nampicuan&Talugtug

Figure 1. Flow chart of data extraction.

Figure 2. Meta-analysis of the adjusted odds ratios for CVD in subjects with airflow obstruction. Forest plot showing the meta-analysis of odds ratios for CVD, adjusting for age, smoking (pack-years and current smoking status), BMI, education and sex in subjects with airflow obstruction compared to those without airflow obstruction. Heterogeneity chi-squared = 27.68, d.f. = 26 (P = 0.374). I-squared (variation in ES attributable to heterogeneity) = 6.1%. Estimate of between-study variance Tau-squared = 0.0095. Test for overall effect: Z = 0.00 (P = 0.999). The following sites could not be included in the analysis due to a low number of subjects reporting CVD or singularity in the data: Blantyre (Malawi), Ife (Nigeria), Mumbai (India), Penang (Malaysia), Pune (India), Srinagar (India).

Figure 3. Meta-analysis of the adjusted odds ratios for hypertension in subjects with airflow obstruction. Forest plot showing the meta-analysis of odds ratios for hypertension, adjusting for age, smoking (pack-years and current smoking status), BMI, education and sex in subjects with airflow obstruction compared to those without airflow obstruction. Heterogeneity chi-squared = 65.31, d.f. = 31 (P = 0.000). I-squared (variation in ES attributable to heterogeneity) = 52.5%. Estimate of between-study variance Tau-squared = 0.0694. Test for overall effect: Z = 1.79 (P = 0.074). The following sites could not be included in the analysis due to a low number of subjects reporting hypertension: Ife (Nigeria).

Figure 4. Meta-analysis of the adjusted odds ratios for diabetes in subjects with airflow obstruction. Forest plot showing the meta-analysis of odds ratios for diabetes, adjusting for age, smoking (pack-years and current smoking status), BMI, education and sex in subjects with airflow obstruction compared to those without airflow obstruction. Heterogeneity chi-squared = 24.24, d.f. = 24 (P = 0.448). I-squared (variation in ES attributable to heterogeneity) = 1.0%. Estimate of between-study variance Tau-squared = 0.0017. Test for overall effect: Z = 3.35 (P = 0.001). The following sites could not be included in the analysis due to a low number of subjects reporting diabetes or singularity in the data: Cotonou (Benin), Guangzhou (China), Ife (Nigeria), NampicuanTalugtug (Philippines), Naryn (Kyrgyztan), Pune(India), Srinagar (India), Uppsala (Sweden).

Figure 5. Meta-analyses of the odds ratios for comorbidities in subjects with airflow obstruction, showing the influence of the threshold to define airflow obstruction and adjusting for covariates. Summary forest plots showing the unadjusted, partly adjusted, and completely adjusted odds ratios (meta-OR) and the 95% CI for A. diabetes, B. hypertension, and C. CVD in subjects with airflow obstruction compared to those without airflow obstruction (left column: FEV₁/FVC < 2.5th percentile, middle column: FEV₁/FVC < 5th percentile, right column: FEV₁/FVC < 0.70). Adjusting for all variables at the same time (as shown bottom of each panel), leaving out one variable for each model (middle of each panel), and running one model without any adjusting variables (as shown in the upper part of each panel). The variables age, smoking (pack-years and current smoking status), BMI, education and sex were analyzed. Details of these meta-analyses are reported in Supplementary Table 4.

Table 2. Association of airflow obstruction with comorbidities stratified by sex, smoking history and gross national income.

	Cardiovascular Disease		Hypertension		Diabetes
	OR	(95% CI)	OR	(95% CI)	OR	(95% CI)
Female	1.08	(0.80–1.46)	1.13	(0.93–1.37)	0.82	(0.61–1.09)
Male	0.97	(0.79–1.20)	1.18	(1.01–1.38)	0.68	(0.49–0.93)
P*	0.576		0.741		0.381
Ever-smokers	0.98	(0.81–1.19)	1.12	(0.92–1.37)	0.77	(0.58–1.03)
Never-smokers	1.16	(0.89–1.53)	1.09	(0.92–1.29)	0.86	(0.59–1.27)
P*	0.317		0.824		0.651
Lower income	0.99	(0.79–1.24)	1.20	(0.96–1.50)	0.71	(0.58–0.87)
High income	1.01	(0.79–1.27)	1.06	(0.91–1.24)	0.852	(0.64–1.13)
P*	0.913		0.379		0.304

* P = 2-sided probability of a difference between strata. Lower income: low- & middle- income economies. Details of these meta-analyses are reported in Supplementary Table 2 and 3.