A simplified approach to estimating the distribution of occasionally-consumed dietary components, applied to alcohol intake

Chernova, Julia; Solis-Trapala, Ivonne

doi:10.1186/s12874-016-0178-3

Table 3 Alcohol intake quantiles estimates

From: A simplified approach to estimating the distribution of occasionally-consumed dietary components, applied to alcohol intake

Quantiles
Age, y	Model	0.1	0.25	0.5	0.75	0.9	0.95
Men
40	A	8.2	29.6	91.1	194	321.8	419.1
	B	11.1	36	97.7	190	301.6	386
	MC1	8.6	32	97.1	190.3	311.4	407.7
	MC5	8.2	29.5	91.3	191.5	312.4	410.9
	MC10	7.9	29.7	91	192	322.7	420.2
	MC50	8.3	30.1	90.6	194.1	321.8	416.2
45	A	9.8	34.2	97.9	198.1	321.3	414.9
	B	13.2	41.1	103.9	193.4	301.2	382.8
	MC1	7.8	32.6	86.1	190.4	306.4	391.5
	MC5	9.7	34.2	96	199.7	317.6	408.4
	MC10	9.4	33.9	97.3	196.1	317.3	416.4
	MC50	9.7	34.6	98	198.6	322.5	414
50	A	11.7	39	104	201	319.5	409.6
	B	15.5	46.3	109.2	195.6	299.6	378.5
	MC1	12.5	43.1	108	199.5	330.1	386.3
	MC5	13	41.3	104.9	203.1	325.1	416.6
	MC10	11.2	37.9	101.7	201.3	320.9	413.3
	MC50	11.4	38.5	103.9	201.7	317.4	407.8
55	A	13.9	43.9	109.2	202.7	316.6	403.2
	B	18.2	51.5	113.6	196.8	297.1	373.2
	MC1	13.5	44.5	108.5	202	301.7	396.1
	MC5	13.3	42.4	107	205.4	318.7	406.4
	MC10	13.5	42.1	105.2	198.4	308.5	390.1
	MC50	13.7	43	108.5	204	319.7	406.8
60	A	16.3	48.9	113.5	203.3	312.7	395.9
	B	21.1	56.8	117	197	293.7	367.1
	MC1	14.5	43.9	107.6	200.4	306.7	375.8
	MC5	15.3	48.7	113.7	203.9	319	408
	MC10	16.4	47.7	111.2	203.2	311.1	392.1
	MC50	15.9	48.9	114.5	204.8	314.7	397.6
65	A	19	53.7	116.9	203	307.9	387.9
	B	24.5	61.5	119.6	196.4	289.4	360.2
Quantiles
Age, y	Model	0.1	0.25	0.5	0.75	0.9	0.95
	MC1	19.4	55	120.4	197.7	303.9	370.1
	MC5	18.5	52.6	115.9	201.8	304	392
	MC10	19.7	54.2	117.6	202.8	311.4	394.1
	MC50	19.2	54.3	118	204.3	308	387.1
Women
40	A	0	4	20.1	71.7	166	251
	B	1.7	6.5	25.2	70.7	143.5	207.4
	MC1	0.9	4	19.7	69.8	156.1	248.2
	MC5	0.8	4	20.2	73.8	167.4	252.8
	MC10	0.8	3.7	19.3	71.6	166.9	253.1
	MC50	0.8	4	19.7	70.5	163.2	249.8
45	A	1	5	24	79.7	176.8	262.7
	B	2.1	8.1	29.7	78.3	153.6	219.3
	MC1	1.2	5.2	26.5	90.9	186.6	256.1
	MC5	1	4.9	23.9	77.4	173.4	258.6
	MC10	1	5.2	24.3	80.9	174.4	255.5
	MC50	1	5	24.1	80.5	176	260.5
50	A	1.3	6.2	28.4	88.1	186.9	273.6
	B	2.6	10	34.6	85.8	163.4	230.6
	MC1	1.2	7	29.9	86	181.8	268.4
	MC5	1.3	6.1	28.2	86.4	182.1	272.3
	MC10	1.4	6.5	29.4	89.8	192.2	279.4
	MC50	1.3	6.2	28.2	88.2	186.5	273.3
55	A	1.6	7.7	33.2	96.1	196.4	283.5
	B	3.3	12.3	39.7	93.2	172.8	241.3
	MC1	1.5	8.3	34.1	95.7	203.3	282.2
	MC5	1.6	7.9	34.2	95.7	195.6	300.1
	MC10	1.6	7.3	32.2	93.9	197.7	286.6
	MC50	1.6	7.6	33.1	95.5	195.7	282.8
60	A	2.1	9.5	38.3	103.8	205.1	292.6
	B	4.2	14.9	44.9	100.4	181.7	251.5
	MC1	2.5	11.3	40.9	109.9	216.9	286.2
	MC5	2.3	9.8	39.2	104.2	209.3	296
Quantiles
Age, y	Model	0.1	0.25	0.5	0.75	0.9	0.95
	MC10	2.3	10.2	40.3	110.6	213.8	301.5
	MC50	2.1	9.6	38.1	103.6	205.9	293
65	A	2.6	11.6	43.5	111.1	213.1	300.7
	B	5.2	17.8	50.2	107.2	190.1	261
	MC1	2.3	11	42.4	115	237.4	302.9
	MC5	2.8	12.5	45.4	112.6	208.4	305.2
	MC10	2.7	11.9	44.9	111.4	214.5	299.9
	MC50	2.6	11.6	43.2	110.7	211.5	303

Models A and B estimate the quantiles of weekly alcohol intake distribution based on the numerical method proposed in the paper. Model A adjusts for the correlation between probability and amount parts; Model B assumes zero correlation between the probability and amount parts. Models MC1, MC5, MC10 and MC50 estimate the quantiles of weekly alcohol intake distribution under the assumptions of model A based on Monte Carlo simulations. The estimates of MC1 are based on 1000 observations, MC5 on 5000 observations, MC10 on 10000 observations and MC50 on 50000 observations per covariate pattern

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ISSN: 1471-2288

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