Skip to main content
Erschienen in: Nutrition Journal 1/2015

Open Access 01.12.2015 | Research

Association of lunch meat consumption with nutrient intake, diet quality and health risk factors in U.S. children and adults: NHANES 2007–2010

verfasst von: Sanjiv Agarwal, Victor L. Fulgoni III, Eric P. Berg

Erschienen in: Nutrition Journal | Ausgabe 1/2015

Abstract

Background

Consumption of lean meat is recommended as part of healthy diet by Dietary Guidelines for Americans, 2010. Lunch meats are precooked or cured meats typically used in sandwiches and are also called as cold cuts or deli meat.

Objective

The purpose of the study was to examine the association of lunch meat consumption with nutrient intake, diet quality, and physiological measures in children (age 2–18 years; n = 5,099) and adults (age 19 years and older; n = 10,216) using a large, nationally representative database.

Methods

Lunch meat consumers were defined as those consuming any amount of lunch meat during a 24-h recall and association with nutrient intake, diet quality (Healthy Eating Index (HEI)-2010 score) and physiological measures were evaluated using the National Health and Nutrition Examination Survey (NHANES), 2007–2010.

Results

The lunch meat consumers (both children and adults) had higher intakes of calories, protein, calcium, potassium, sodium and saturated fat (for adults only) compared to non-consumers. Lunch meat intake was also associated with higher intake of meat/poultry/fish food group in both children and adult consumers than non-consumers. There was no difference in total HEI-2010 scores comparing lunch meat consumers and non-consumers in children or adults. However, HEI components scores for total fruit, whole fruit (children only), whole grains, dairy and total protein foods were significantly higher, and for greens & beans (adults only), seafood and plant protein, fatty acid ratio and sodium were significantly lower in children and adult lunch meat consumers compared to non-consumers. There were no significant differences in physiological measures or in the odds ratios of health related conditions between lunch meat consumers and non-consumers in children or adults.

Conclusions

The results of this study may provide insight into how to better utilize lunch meats in the diets of U.S. children and adults.
Hinweise

Competing interests

SA and VLF are nutrition consultants and provide services to food industry. EPB is a faculty at North Dakota State University and also serves as academic consultant on the Food Safety, Human Nutrition, and Pork Quality Committee, National Pork Board.

Authors’ contributions

All authors participated in data analysis and interpretation. SA drafted the manuscript and all authors participated in revising and finalizing the manuscript. All authors read and approved the final manuscript.
Abkürzungen
BMI
Body Mass Index
HEI
Healthy Eating Index
MUFA
Mono unsaturated fatty acids
NHANES
National Health and Nutrition Examination Survey
PUFA
Poly unsaturated fatty acids
SEM
Standard errors of the mean
SFA
Saturated fatty acids

Background

The Dietary Guidelines for Americans, 2010 recommend consumption of lean meat as part of an overall healthy diet [1]. MyPlate (ChooseMyPlate.gov) recommends intake from the meat and beans group ranges from 2 to 6.5 ounce (oz.) equivalents depending on age, gender, and physical activity [2]. Meat is an important source of high quality protein and several key micronutrients including iron, zinc, and B-vitamins in American diet [18]. The bioavailability of iron and folate from meat is higher than from plant products such as grains and leafy green vegetables [3, 9].
Lunch meats are precooked or cured meats that are sliced for use in sandwich or salad toppings. They are also referred to as “cold cuts” or “deli meat”. There are three types of lunch meats: a) Whole cut – a section of whole muscle that is cooked, flavored/spiced and sliced such as roast beef or corned beef; b) Sectioned/formed –meat trimmings or flakes bound together to form restructured meat products such as multi-part turkey breast or cooked ham; and c) Processed meat – which include fine or coarsely ground meat products such as sausages or emulsified products such as bologna and hot dogs. The recently released Scientific Report of the Dietary Guidelines Advisory Committee 2015 indicated that dietary patterns consisting of lower consumption of red and processed meat were associated with positive health outcomes [10].
The purpose of the present study was to assess the association of lunch meat intake with nutrient intake, diet quality and physiological measures associated with health risk factors in children and adults using a large nationally representative database.

Methods

Subjects

National Health and Nutrition Examination Survey (NHANES), a large dietary survey of a nationally representative sample of the non-institutionalized US population, was used to assess lunch meat intake [11]. The NHANES data are collected and released by the National Center for Health Statistics (NCHS) of the Center for Disease Control and Prevention, every two years. All participants or proxies (i.e., parents or guardians) provided written informed consent and the Research Ethics Review Board at the NCHS approved the survey protocol. Dietary intake data with reliable 24-h recall dietary interviews (day 1 data only) using United States Department of Agriculture’s (USDA) automated multiple-pass method were used. The data from NHANES 2007–2008 and 2009–2010 were combined for the analyses [11]. The combined sample included 5,099 children age 2–18 years old and 10,216 adults age 19 years and older excluding pregnant and/or lactating females and those with incomplete or unreliable 24-h recall data.

Estimation of intake

Lunch meat intakes were assessed using a total of thirty nine USDA food codes for typical lunch meats (Table 1) [12, 13]. These food codes were also used to find food codes containing luncheon meat as an ingredient. Foods such as stews containing small amounts (<7 %) of luncheon meats as ingredient were not considered as lunch meat. Lunch meat consumers were defined as those consuming any amount of lunch meat (from 39 food codes) during a 24-h recall. Energy and nutrient intake were determined using the USDA Nutrient Database for Standard Reference Releases 22 and 24 in conjunction with the Food & Nutrient Database for Dietary Studies versions 4.1 and 5.0, for NHANES 2007–2008 and NHANES 2009–2010 participants respectively [1215]. The USDA Food Patterns Equivalents Database (FPED) [16] was used to calculate intake MyPlate [17] servings. The FPED translates dietary recall data into equivalent servings of the seven MyPlate major food groups and corresponding subgroups. The number of MyPlate servings was aggregated over all foods consumed during the 24-hour recall to calculate the MyPlate food group intakes per day.
Table 1
USDA food codes for lunch meats and their description [12, 13]
Food code
Description
Food code
Description
21420100
Beef, sandwich steak (flaked, formed, thinly sliced)
25230310
Chicken or turkey loaf, prepackaged or deli, luncheon meat
21603000
Beef, pastrami (beef, smoked, spiced)
25230410
Ham loaf, luncheon meat
22311450
Ham, prosciutto
25230430
Ham and cheese loaf
25220010
Cold cut, NFS
25230510
Ham, luncheon meat, chopped, minced, pressed, spiced, not canned
25220390
Bologna, beef, low fat
25230520
Ham, luncheon meat, chopped, minced, pressed, spiced, low fat, not canned
25220400
Bologna, pork and beef
25230530
Ham and pork, luncheon meat, chopped, minced, pressed, spiced, canned
25220410
Bologna, NFS
25230540
Ham, pork and chicken, luncheon meat, chopped, minced, pressed, spiced, canned
25220420
Bologna, Lebanon
25230550
Ham, pork, and chicken, luncheon meat, chopped, minced, pressed, spiced, canned, reduced sodium
25220430
Bologna, beef
25230560
Liverwurst
25220440
Bologna, turkey
25230610
Luncheon loaf (olive, pickle, or pimiento)
25220470
Bologna, beef, lower sodium
25230710
Sandwich loaf, luncheon meat
25220480
Bologna, chicken, beef, and pork
25230790
Turkey ham, sliced, extra lean, prepackaged or deli, luncheon meat
25220500
Bologna, beef and pork, low fat
25230800
Turkey ham
25221500
Salami, NFS
25230810
Veal loaf
25221510
Salami, soft, cooked
25230820
Turkey pastrami
25221520
Salami, dry or hard
25230840
Turkey salami
25230110
Luncheon meat, NFS
25230900
Turkey or chicken breast, prepackaged or deli, luncheon meat
25230210
Ham, sliced, prepackaged or deli, luncheon meat
25230905
Turkey or chicken breast, low salt, prepackaged or deli, luncheon meat
25230220
Ham, sliced, low salt, prepackaged or deli, luncheon meat
25231110
Beef, sliced, prepackaged or deli, luncheon meat
25230230
Ham, sliced, extra lean, prepackaged or deli, luncheon meat
  

Estimation of diet quality

Diet quality was calculated using the Healthy Eating Index (HEI) -2010 which has 12 components, each representing a different aspect of diet quality [18]. HEI - 2010 scores were estimated using day 1 dietary intake data. The SAS code used to calculate HEI - 2010 scores was downloaded from the USDA website [19].

Estimation of physiological markers of risk

Health indices evaluated included body weight, body mass index (BMI) and Z score for children [20], as well as BMI, waist circumference, blood pressure, fasting plasma glucose, fasting plasma insulin, c–reactive protein, fasting triglycerides, total cholesterol, LDL-cholesterol (fasting), HDL-cholesterol, and apolipoprotein B, and risk of metabolic syndrome for adults using NHANES standard protocols [11]. For a variety of reasons, not all individuals have values for all tests (see tables for sample numbers). Metabolic syndrome was defined using the NHLBI Adult Treatment Panel III criteria [21], namely having three or more of the following risk factors: abdominal obesity (waist circumference >102 cm for males and >88 cm for females); hypertension (BP systolic ≥130 mmHg or BP diastolic ≥85 mmHg or taking anti-hypertensive medications); low HDL-cholesterol (<40 mg/dL for males and <50 mg/dL for females); high triglycerides (≥150 mg/dL or taking anti-hyperlipidemic medications); high fasting glucose (≥110 mg/dL or taking insulin or other hypoglycemic agents).

Statistical analysis

All analyses were performed using SAS 9.2 (SAS Institute, Cary, NC) and SUDAAN 11 (RTI, Research Triangle Park, NC) to adjust the variances for the complex sample design of NHANES and thus survey weights, strata and primary sampling units were used in all calculations. Day one dietary weights were used in all intake analyses, while the Mobile Examination Center weights were used for physiological variables except where the outcome was a fasting lab variable in which case fasting subsample weights were used. Least square means (Mean), standard errors of the mean (SEM), via regression analyses were determined for energy and nutrient intakes, food group intake, diet quality, and physiological markers of metabolic disease risk in lunch meat consumers and non-consumers. Food group/nutrient intakes were adjusted for age (even within each age group), gender, ethnicity, poverty income ratio, self-reported physical activity level, smoking status, alcohol intake (only for adults), and energy intake (except for energy intake). Diet quality was adjusted for the same covariates but without energy intake as HEI scores are already adjusted for energy intake. Physiological variables were adjusted for age, gender, ethnicity, poverty-income ratio, self-reported physical activity level, smoking status, alcohol intake (only for adults) and BMI (for non-weight related variables).

Results

Approximately 19.4 % adults (age 19 years and older) and 17.8 % children (age 2–18 years) were lunch meat consumers. In both children and adults, there were no major demographic differences between lunch meat consumers and non-consumers except that there were 12 % fewer adult female consumers (46.2 % female adult consumers versus 52.6 % female non-consumers, P < 0.0001).
There were significant differences in nutrient intakes between the lunch meat consumers and the non-consumers (Table 2). Compared with non-consumers in children, lunch meat consumers had significantly higher (P < 0.01) intakes of calories (7.3 %), and energy adjusted daily intakes of protein (8.3 %), calcium (13 %), potassium (5.5 %), thiamin (7.3 %) and sodium (15.6 %). Similarly adult lunch meat consumers also had significantly higher (P < 0.01) intakes of calories (4.4 %), and energy adjusted intakes of protein (6.3 %), saturated fatty acids (3.6 %), calcium (14.3 %), potassium (6.2 %), thiamin (11.1 %), and sodium (18.3 %) compared to adult non-consumers. Adult lunch meat consumers also had significantly lower (P < 0.01) intakes of monounsaturated fatty acids (MUFA) (−3.6 %) and polyunsaturated fatty acids (PUFA) (−4.5 %) compared to non-consumers. The intake of other nutrients was not significantly different among lunch meat consumers and non-consumers (Table 2).
Table 2
Energy and nutrient intakes in children (n = 5099) and adult (n = 10216) lunch meat consumers and non-consumers (NHANES 2007–2010, gender combined data). Values are means ± SEM. Values are adjusted for age, gender, ethnicity, poverty income ratio, physical activity level, current smoking status, alcohol (only for adults), and kcal (except for energy)
Variables
Children (2–18 years old)
Adults (19 years and older)
Non-consumers
Consumers
P Value for difference
Non-consumers
Consumers
P Value for difference
Energy (kcal)
1873 ± 17
2009 ± 42
0.0022
2115 ± 14
2209 ± 27
0.0029
Protein (gm)
66.6 ± 0.4
72.1 ± 1.0
<0.0001
81.6 ± 0.4
86.8 ± 0.8
<0.0001
Carbohydrate (gm)
255 ± 1
250 ± 2
0.0236
258 ± 1
254 ± 2
0.0122
 Dietary fiber (gm)
13.0 ± 0.2
12.9 ± 0.2
0.7796
16.5 ± 0.3
15.7 ± 0.3
0.0147
 Total sugars (gm)
127 ± 1.3
122 ± 2
0.0201
118 ± 1
114 ± 2
0.0253
Total fat (gm)
69.6 ± 0.4
69.6 ± 1.0
0.9627
80.3 ± 0.4
79.6 ± 0.6
0.2920
 MUFA (gm)
25.1 ± 0.2
24.2 ± 0.5
0.0647
29.4 ± 0.2
28.4 ± 0.3
0.0016
 PUFA (gm)
14.0 ± 0.2
13.8 ± 0.3
0.4677
17.5 ± 0.1
16.8 ± 0.2
0.0008
 SFA (gm)
24.4 ± 0.2
25.3 ± 0.6
0.1387
26.3
27.2 ± 0.3
0.0021
Cholesterol (mg)
210 ± 3
228 ± 8
0.0269
287 ± 4
277 ± 5
0.0944
Calcium (mg)
1006 ± 12
1136 ± 29
0.0006
953 ± 9
1090 ± 16
<0.0001
Iron (mg)
13.5 ± 0.2
13.8 ± 0.4
0.3901
15.2 ± 0.1
15.3 ± 0.2
0.5789
Magnesium (mg)
228 ± 2
235 ± 5
0.1177
299 ± 3
302 ± 3
0.4044
Potassium (mg)
2141 ± 22
2258 ± 37
0.0020
2674 ± 22
2839 ± 26
<0.0001
Sodium (mg)
2966 ± 28
3427 ± 52
<0.0001
3494 ± 18
4132 ± 43
<0.0001
Vitamin A (μg)
592 ± 10
591 ± 19
0.9744
621 ± 9
637 ± 15
0.2720
ß-carotene (μg)
1171 ± 61
1136 ± 137
0.8192
2081 ± 62
2002 ± 116
0.4936
Thiamin (mg)
1.5 ± 0.02
1.6 ± 0.03
0.0012
1.6 ± 0.02
1.8 ± 0.03
<0.0001
Total Folate (μg)
360 ± 5
361 ± 17
0.9696
409 ± 5
403 ± 6
0.4370
Vitamin B6 (mg)
1.7 ± 0.03
1.8 ± 0.1
0.2082
2.0 ± 0.02
2.1 ± 0.04
0.0302
Vitamin C (mg)
78.6 ± 1.9
86.5 ± 4.4
0.0763
86.2 ± 2.1
83.5 ± 2.3
0.2940
MUFA monounsaturated fatty acids, PUFA polyunsaturated fatty acids, SFA saturated fatty acids
Intake of lunch meat was also associated with significant differences (P < 0.01) in specific MyPlate food groups (Table 3). Significantly higher intakes of meat/poultry/fish (31.8 %) and whole grain (37.1 %), and lower intake of added sugars (−7.5 %) were observed among children consuming lunch meats compared to non-consumers. Among adults, consumers of lunch meat had higher intakes of meat/poultry/fish (30.6 %), whole grain (30.7 %), dairy (17.9 %) and grains (5.9 %), and lower intake of vegetables (−7.6 %) compared to adult non-consumers.
Table 3
Intake of MyPlate food groups in children (n = 5099) and adult (n = 10216) lunch meat consumers and non-consumers (NHANES 2007–2010, gender combined data). Values are means ± SEM. Values are adjusted for age, gender, ethnicity, poverty income ratio, physical activity level, current smoking status, alcohol (only for adults), and kcal
Variables
Children (2–18 years old)
Adults (19 years and older)
Non-consumers
Consumers
P Value for difference
Non-consumers
Consumers
P Value for difference
Total Fruit (cup eq.)
1.08 ± 0.04
1.23 ± 0.06
0.0102
0.99 ± 0.03
1.07 ± 0.04
0.0241
 Whole Fruit (cup eq.)
0.67 ± 0.04
0.78 ± 0.06
0.0252
0.67 ± 0.02
0.76 ± 0.03
0.0318
 Fruit Juice (cup eq.)
0.41 ± 0.02
0.44 ± 0.04
0.3352
0.31 ± 0.01
0.31 ± 0.03
0.9484
Total Vegetable (cup eq.)
0.90 ± 0.03
0.81 ± 0.03
0.0362
1.58 ± 0.03
1.46 ± 0.03
0.0042
Total Grain (oz eq.)
6.32 ± 0.07
6.67 ± 0.15
0.0286
6.37 ± 0.06
6.75 ± 0.10
0.0027
 Whole Grain (oz eq.)
0.53 ± 0.02
0.73 ± 0.04
0.0003
0.72 ± 0.03
0.94 ± 0.04
<0.0001
Total Dairy (cup eq.)
2.17 ± 0.04
2.33 ± 0.10
0.2019
1.61 ± 0.02
1.90 ± 0.04
<0.0001
 Milk (cup eq.)
1.44 ± 0.03
1.25 ± 0.05
0.0129
0.85 ± 0.02
0.86 ± 0.03
0.9151
Meat/Poultry/Fish (oz eq.)
3.21 ± 0.08
4.23 ± 0.12
<0.0001
4.70 ± 0.06
6.14 ± 0.08
<0.0001
Added Sugar (tsp eq.)
19.4 ± 0.3
17.9 ± 0.4
0.0092
18.5 ± 0.4
17.5 ± 0.5
0.0264
Despite some differences in food groups intake, there was no difference in dietary quality (measured by the HEI-2010) comparing lunch meat consumers and non-consumers for children (HEI-2010 scores difference between consumers and non-consumers: −0.30, P = 0.6187) or adults (HEI-2010 scores difference between consumers and non-consumers: −0.61, P = 0.2010) (Table 4). When the data were further analyzed for different age groups for children and adults: young children age 2–9 years, adolescent age 9–19 years; adults 19–50 years and adults 51 years and older; and for males and females separately there were still no significant differences (P > 0.01) in HEI 2010 scores between consumers and non-consumers (Table 4).
Table 4
Healthy Eating Index (HEI) – 2010 total score for children and adult lunch meat consumers and non-consumers (NHANES 2007–2010) by age and gender subgroups. Values are means ± SEM. Values are adjusted for age, gender, ethnicity, poverty income ratio, physical activity level, current smoking status, alcohol (only for adults), and kcal
Population subgroup
N
Total HEI 2010 score
Non-consumer
Consumer
P Value
Children age 2–18 years
 Gender combined
5099
46.02 ± 0.41
45.71 ± 0.56
0.6187
 Female
2455
46.14 ± 0.54
46.44 ± 0.74
0.7489
 Male
2644
45.88 ± 0.49
45.06 ± 0.83
0.3664
Young Children age 2–8 years
 Gender combined
2476
50.00 ± 0.43
48.53 ± 0.71
0.0782
 Female
1163
49.96 ± 0.64
49.39 ± 0.92
0.6418
 Male
1313
50.04 ± 0.57
47.32 ± 1.24
0.0776
Adolescent age 9–18 years
 Gender combined
2623
42.92 ± 0.52
43.75 ± 0.85
0.3518
 Female
1292
43.44 ± 0.70
44.55 ± 1.20
0.4152
 Male
1331
42.36 ± 0.63
42.99 ± 1.00
0.5198
Adults age 19 years & older
 Gender combined)
10216
49.40 ± 0.43
48.79 ± 0.51
0.2010
 Female
5116
50.60 ± 0.56
50.54 ± 0.73
0.9387
 Male
5100
48.12 ± 0.38
47.00 ± 0.54
0.0193
Adults age 19–50 years
 Gender combined
5359
46.79 ± 0.48
47.19 ± 0.70
0.5271
 Female
2703
47.64 ± 0.63
48.85 ± 1.00
0.2401
 Male
2656
45.95 ± 0.48
45.65 ± 0.82
0.6456
Adults age 51 years & older
 Gender combined
4857
53.24 ± 0.53
51.23 ± 0.68
0.0124
 Female
2413
54.64 ± 0.58
52.95 ± 0.82
0.1083
 Male
2444
51.61 ± 0.54
49.30 ± 0.95
0.0319
Although the total HEI 2010 was similar for lunch meat consumers and non-consumers among children and adults, there were differences in the scores for components of HEI 2010 (Table 5). In children age 2–19 years, HEI components scores were significantly higher (P < 0.01) for total fruit (12.6 %), whole fruit (17.4 %), whole grains (30.6 %), dairy (9.0 %), and total protein foods (18.8 %) in lunch meat consumers while component scores for seafood and plant protein (−25.6 %), fatty acid ratio (−18.5 %) and sodium (−38.3 %) were significantly lower (P < 0.01) compared to non-consumers. Similarly, among adults, the HEI components scores were significantly higher (P < 0.01) for total fruit (9.1 %), whole grains (31.1 %), dairy (16.2 %), and total protein foods (9.8 %) in lunch meat consumers while component scores for greens and beans (−19.0 %), seafood and plant protein (−18.8 %), fatty acid ratio (−12.8 %) and sodium (−41.8 %) were significantly lower (P < 0.01) compared to non-consumers (Table 5).
Table 5
Healthy Eating Index (HEI) – 2010 total score and component scores of children (n = 5099) and adult (n = 10216) lunch meat consumers and non-consumers (NHANES 2007–2010 gender combined data). Values are means ± SEM. Values are adjusted for age, gender, ethnicity, poverty income ratio, physical activity level, current smoking status, alcohol (only for adults), and kcal
Variables
Children (2–18 years old)
Adults (19 years and older)
Non-consumers
Consumers
P Value for difference
Non-consumers
Consumers
P Value for difference
HEI-2010 Total Score
46.02 ± 0.41
45.71 ± 0.56
0.6187
49.40 ± 0.43
48.79 ± 0.51
0.2010
Component 1 (Total Vegetables)
2.10 ± 0.04
1.95 ± 0.08
0.0821
3.05 ± 0.04
2.89 ± 0.05
0.0100
Component 2 (Greens & Beans)
0.68 ± 0.05
0.52 ± 0.08
0.0902
1.28 ± 0.05
1.03 ± 0.06
0.0001
Component 3 (Total Fruit)
2.51 ± 0.06
2.83 ± 0.11
0.0059
2.13 ± 0.04
2.32 ± 0.06
0.0039
Component 4 (Whole Fruit)
2.24 ± 0.07
2.63 ± 0.15
0.0095
2.07 ± 0.05
2.28 ± 0.08
0.0212
Component 5 (Whole Grains)
1.97 ± 0.07
2.57 ± 0.13
0.0007
2.23 ± 0.08
2.93 ± 0.10
<0.0001
Component 6 (Dairy)
6.97 ± 0.09
7.60 ± 0.15
0.0013
5.10 ± 0.07
5.92 ± 0.11
<0.0001
Component 7 (Total Protein Foods)
3.46 ± 0.04
4.11 ± 0.05
<0.0001
4.16 ± 0.02
4.57 ± 0.02
<0.0001
Component 8 (Seafood & Plant Protein)
1.37 ± 0.04
1.02 ± 0.09
0.0013
2.07 ± 0.04
1.68 ± 0.07
<0.0001
Component 9 (Fatty Acid Ratio)
3.88 ± 0.07
3.16 ± 0.16
0.0004
4.98 ± 0.06
4.34 ± 0.13
0.0002
Component 10 (Sodium)
5.17 ± 0.11
3.19 ± 0.17
<0.0001
4.39 ± 0.06
2.55 ± 0.09
<0.0001
Component 11 (Refined Grains)
5.30 ± 0.09
5.00 ± 0.20
0.1818
6.21 ± 0.06
6.05 ± 0.15
0.2908
Component 12 (SoFAAS Calories)
10.36 ± 0.13
11.14 ± 0.31
0.0224
11.73 ± 0.17
12.22 ± 0.19
0.0167
There were no differences in any studied physiological measures (body weight, waist circumference, body mass index, systolic blood pressure, diastolic blood pressure, fasting plasma glucose, fasting plasma insulin, C-reactive protein, fasting triglycerides, total cholesterol, LDL- cholesterol, HDL-cholesterol, and apolipoprotein B) associated with lunch meat consumption in children age 2–18 years and in adults age 19 years and older (Table 6). The differences between consumers and non-consumers remained non-significant (P > 0.01) when the data was further analyzed for different age groups for children and adults: young children age 2–9 years, adolescent age 9–19 years; adults 19–50 years and adults 51 years and older; and for males and females (data not presented).
Table 6
Association of lunch meat consumption with physiological measures in children and adults - NHANES 2007–2010. Values are means ± SEM. Values are adjusted for age, gender, ethnicity, poverty income ratio, physical activity level, current smoking status, alcohol (only for adults) and weight (only for variable not related to weight)
Physiological variables
N
Non-consumer
Consumer
P Value
Children age 2–18 years
 BMI Z Score
5046
0.44 ± 0.03
0.48 ± 0.05
0.4464
Adults age 19 years and older
 Weight (kg)
10,108
82.19 ± 0.35
82.08 ± 0.65
0.8859
 Body Mass Index (kg/m2)
10,097
28.69 ± 0.12
28.73 ± 0.21
0.8631
 Waist Circumference (cm)
9,821
98.10 ± 0.30
97.98 ± 0.53
0.8631
 BP Diastolic (mm Hg)
9,761
70.63 ± 0.37
70.42 ± 0.44
0.5349
 BP Systolic (mm Hg)
9,802
121.28 ± 0.29
121.51 ± 0.43
0.6721
 Total cholesterol (mg/dL)
9,604
196.95 ± 0.73
196.35 ± 1.44
0.6160
 LDL-cholesterol (mg/dL)
4,280
116.68 ± 0.78
113.83 ± 1.41
0.0539
 HDL-cholesterol (mg/dL)
9,604
52.52 ± 0.33
52.57 ± 0.42
0.8991
 Triglyceride (mg/dL)
4,359
129.81 ± 1.91
131.96 ± 3.87
0.6182
 Apolipoprotein (B) (mg/dL)
4,357
92.34 ± 0.66
90.47 ± 1.03
0.0620
 C-reactive protein (mg/dL)
9,636
0.37 ± 0.01
0.42 ± 0.04
0.2105
 Glucose, plasma (mg/dL)
4,391
104.59 ± 0.61
106.42 ± 1.29
0.2162
 Insulin (μU/mL)
4,332
12.70 ± 0.23
12.28 ± 0.27
0.2582
The odds ratios of health related conditions were also similar (overlapping 95 % CI) for lunch meat consumers compared to non-consumers for both children and adults (Table 7). Lunch meat consumers did not show any significant differences in odds ratios compared with non-consumers even when the data was further analyzed for different age groups for children: young children age 2–9 years, adolescent age 9–19 years; for adults: age 19–50 years and 51 years and older; and for males and females (data not presented).
Table 7
Association of lunch meat consumption with odds ratios of weight/waist status and other risk factors in children and adults - NHANES 2007–2010. Values are adjusted for age, gender, ethnicity, poverty income ratio, physical activity level, current smoking status, alcohol (for adults only), and weight (only for variable not related to weight)
Variables
N
Odds ratio (95 % CI)
Non-consumer
Consumer
P Value
Children age 2–18 years
 Obese
5046
1.00
1.14 (0.90, 1.44)
0.2577
 Overweight
5046
1.00
1.01 (0.70, 1.47)
0.9560
 Overweight or Obese
5046
1.00
1.09 (0.85, 1.40)
0.4693
Adults age 19 years and older
 Obese
10,097
1.00
0.97 (0.82, 1.16)
0.7518
 Overweight
10,097
1.00
0.89 (0.75, 1.04)
0.1391
 Overweight or Obese
10,097
1.00
0.86 (0.74, 1.01)
0.0582
 Waist Circumference Elevated
9,821
1.00
0.88 (0.73, 1.05)
0.1519
 BP Elevated
9,971
1.00
0.96 (0.78, 1.18)
0.6777
 HDL Reduced
9,808
1.00
1.01 (0.88, 1.15)
0.9306
 LDL Elevated
4,359
1.00
0.88 (0.70, 1.10)
0.2594
 Triglycerides Elevated
4,420
1.00
1.03 (0.83, 1.28)
0.7786
 Glucose Elevated
4,443
1.00
1.13 (0.91, 1.40)
0.2699
 Metabolic Syndrome
7,229
1.00
0.98 (0.75, 1.28)
0.8699

Discussion

This is the first report to investigate lunch meat consumption in the U.S. population and explore its relationships with nutrient intake, diet quality and physiological markers of health. In the present study, we combined NHANES 2007–2008 and NHANES 2009–2010 data and the combined data set provided a sample size of over 15 thousand adults and children. Lunch meats, also known as deli meat or cold cuts, are precooked or cured meat that are sliced and used to make a convenient sandwich filling or salad topping. The NHANES 2007–2010 data showed that almost one-fifth of the population (18 % children age 2–18 and 19 % adults age 19 years and older) consumed lunch meat on the day of the recall.
Both adults and children consumers of lunch meat consumed significantly more calories as well as protein compared to their respective non-consumers. Additionally, they consumed more energy adjusted calcium, potassium and thiamine compared to non-consumers. Calcium and potassium are termed as “nutrients of concern” by the Dietary Guidelines for Americans, 2010 [1]. Current intake of calcium is estimated to be below the Estimated Average Requirement for over 40 % of the population and only about 3 % population is currently consuming more than the Adequate Intake for potassium [10]. Adequate calcium status is important for optimal bone health and potassium helps lower the blood pressure. Dietary Guidelines for Americans, 2010 has recommended increasing intake of calcium and potassium [1]. Meat (especially lean meat) is considered as one of the most nutrient dense food [6]. Lunch meat consumers also had higher intakes of sodium compared to non-consumers. Excessive sodium intake has been related to high prevalence of high blood pressure [1]. Sodium intake estimated in this study was higher than the recommended 2,300 mg for both adult and children, irrespective of their being consumers or non-consumers. Potassium lowers blood pressure by blunting the adverse effects of sodium on blood pressure. However, it should be noted there were no significant differences in blood pressure between consumers and non-consumers for both adults and children.
The HEI 2010 scores of lunch meat consumers were not significantly different from those of non-consumers for both adults and children. The HEI is a measure of diet quality that indicates compliance/adherence of the diets to the recommendations of Dietary Guidelines for Americans, 2010. HEI is commonly used to evaluate diets including subpopulations [22] and food environments [23], to assess changes in the diet quality over time [24] and the efficacy of dietary interventions, and to validate other nutrition research tools and indexes [25]. It has also been used in recent research to understand relationships between nutrients/foods/dietary patterns and health-related outcomes [2629]. Lunch meat consumers had similar HEI 2010 scores as non-consumers and the differences in HEI 2010 scores remained non-significant even when the data was further analyzed by age (young children, adolescent, adults and older adults) and gender groups (males and females) indicating that the diet quality of lunch meat consumers were similar to non-consumers for every age/gender group. These results suggest that lunch meats do not necessarily decrease average diet quality of adults and children. HEI 2010 has 12 components (9 for adequacy and 3 for moderation) each of which relate to the key recommendations of the Dietary Guidelines for Americans, 2010. Although the total HEI scores were not different for lunch meat consumers compared to non-consumers, there were some differences in the subcomponent scores which may provide insight into incorporating lunch meats into diets to help align with Dietary Guidelines Recommendations. For example, lower sodium lunch meat options may be considered and it appears that the use of cheese and whole grains are more common in lunch meat consumers thus improving HEI subcomponent scores for dairy and whole grains, respectively.
In the current study, lunch meat intake was not associated with any physiological measurements including BMI, blood pressure, blood lipids or blood sugar. The recently released Scientific Report of the Dietary Guidelines Advisory Committee 2015 indicated that dietary patterns consisting of lower consumption of red and processed meat were associated with positive health outcomes [10]. In an abstract the International Agency for Research on Cancer experts indicated that 34,000 to 50,000 cancer deaths per year worldwide may be attributable to diets high in processed meat and red meat respectively while air pollution, alcohol intake and tobacco smoking are responsible for 200,000, 600,000 and 1 million deaths per year worldwide respectively [30, 31]. The expert report concluded that each 50 g portion of processed meat eaten daily may increase the risk of colorectal cancer by 18 %, [30, 31]. It is impossible to accurately discern the contribution of one single food consumed with causation of cancer because it is impossible to separate an individual food from the confounding interactions of other potential carcinogenic “hazards” experienced over the course of a lifetime. Intake of processed meat was found to be associated with a higher risk of coronary heart disease (CHD) and type-2 diabetes [32]. In a meta-analysis, consumption of processed meats was associated with higher incidence of CHD and diabetes mellitus [33]. High intake of processed meat was also implicated with increased risk of early death, in particular due to cardiovascular diseases and cancer, in a recently published European epidemiological study [34]. However, most observational studies reported only a small increase in relative risk [6]. Industry efforts for the past 10 years have focused on simplification of ingredient lists. This “clean labeling” effort has resulted in significant changes regarding processing techniques applied to product development of luncheon meats. In the present study, we did not find any significant differences in physiological measures or in the odds ratio of all studied health related conditions between lunch meat consumers and non-consumers (in fact, lunch meat consumers had better average physiological measures for lipids and overweight/obesity risk in our findings.) Whether the lack of significant effect on physiological parameters is a result of using NHANES, an observational study; effect of presence of other dietary components such as fruits and vegetables, whole grain etc. in the diet of consumers; or whether lunch meats have evolved since the previously mentioned studies were published will have to await further research.
A limitation of this study is that cross-sectional studies cannot be used to determine cause and effect. Additionally, 24-h dietary recalls rely on participants’ memory to self-report dietary intakes; and therefore data are subject to misreporting. Also the data used in this study was based on single 24-h dietary recall. Strengths of this study included the use of large nationally representative sample achieved through combining several sets of NHANES data releases and adjusting for numerous covariates, but even with these covariates some residual confounding may still exist.
Future research might consider comparing lunch meat consumers, with consumers of other meats and/or non-consumers of meat. Additionally, when further data are available it might also be meritorious to conduct analyses comparing particular types of lunch meats (e.g., whole cut versus sectioned/formed, versus processed meat). Other work might examine further other items consumed with lunch meats and whether more healthy items could be identified.

Conclusion

In conclusion, results from this study suggest that lunch meat intake did not affect the overall diet quality while differences in certain subcomponents scores (dairy, whole grains and sodium) suggest there may be ways to incorporate lunch meats into healthy dietary patterns.

Acknowledgement

The present study was funded by North American Meat Institute.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://​creativecommons.​org/​licenses/​by/​4.​0/​), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://​creativecommons.​org/​publicdomain/​zero/​1.​0/​) applies to the data made available in this article, unless otherwise stated.

Competing interests

SA and VLF are nutrition consultants and provide services to food industry. EPB is a faculty at North Dakota State University and also serves as academic consultant on the Food Safety, Human Nutrition, and Pork Quality Committee, National Pork Board.

Authors’ contributions

All authors participated in data analysis and interpretation. SA drafted the manuscript and all authors participated in revising and finalizing the manuscript. All authors read and approved the final manuscript.
Literatur
1.
Zurück zum Zitat U.S. Department of Health and Human Services and USDA. Dietary Guidelines for Americans, 2010. 7th ed. Washington, DC: GPO; 2011. U.S. Department of Health and Human Services and USDA. Dietary Guidelines for Americans, 2010. 7th ed. Washington, DC: GPO; 2011.
3.
Zurück zum Zitat Biesalski HK. Meat as a component of a healthy diet - are there any risks or benefits if meat is avoided in the diet? Meat Sci. 2005;70:509–24.CrossRef Biesalski HK. Meat as a component of a healthy diet - are there any risks or benefits if meat is avoided in the diet? Meat Sci. 2005;70:509–24.CrossRef
4.
Zurück zum Zitat O'Neil CE, Zanovec M, Keast DR, Fulgoni 3rd VL, Nicklas TA. Nutrient contribution of total and lean beef in diets of US children and adolescents: National Health and Nutrition Examination Survey 1999–2004. Meat Sci. 2011;87:250–6.CrossRef O'Neil CE, Zanovec M, Keast DR, Fulgoni 3rd VL, Nicklas TA. Nutrient contribution of total and lean beef in diets of US children and adolescents: National Health and Nutrition Examination Survey 1999–2004. Meat Sci. 2011;87:250–6.CrossRef
5.
Zurück zum Zitat Murphy MM, Spungen JH, Bi X, Barraj LM. Fresh and fresh lean pork are substantial sources of key nutrients when these products are consumed by adults in the United States. Nutr Res. 2011;31:776–83.CrossRef Murphy MM, Spungen JH, Bi X, Barraj LM. Fresh and fresh lean pork are substantial sources of key nutrients when these products are consumed by adults in the United States. Nutr Res. 2011;31:776–83.CrossRef
7.
Zurück zum Zitat Pereira PMCC, Vicente AFRB. Meat nutritional composition and nutritive role in the human diet. Meat Sci. 2013;93:586–92.CrossRef Pereira PMCC, Vicente AFRB. Meat nutritional composition and nutritive role in the human diet. Meat Sci. 2013;93:586–92.CrossRef
8.
Zurück zum Zitat Wyness L. The role of red meat in the diet: nutrition and health benefits. Proc Nutr Soc. 2015;8:1-6. [Epub ahead of print]. Wyness L. The role of red meat in the diet: nutrition and health benefits. Proc Nutr Soc. 2015;8:1-6. [Epub ahead of print].
9.
Zurück zum Zitat Nohr D, Biesalski HK. 'Mealthy' food: meat as a healthy and valuable source of micronutrients. Animal. 2007;1:309-316.CrossRef Nohr D, Biesalski HK. 'Mealthy' food: meat as a healthy and valuable source of micronutrients. Animal. 2007;1:309-316.CrossRef
12.
Zurück zum Zitat USDA, Agricultural Research Service, Food Surveys Research Group: Food and Nutrient Database for Dietary Studies, 4.1. Beltsville: 2010. USDA, Agricultural Research Service, Food Surveys Research Group: Food and Nutrient Database for Dietary Studies, 4.1. Beltsville: 2010.
13.
Zurück zum Zitat Ahuja JKA, Montville JB, Omolewa-Tomobi G, Heendeniya KY, Martin CL, Steinfeldt LC, et al. USDA Food and Nutrient Database for Dietary Studies, 5.0. Beltsville: Department of Agriculture, Agricultural Research Service, Food Surveys Research Group; 2012. Ahuja JKA, Montville JB, Omolewa-Tomobi G, Heendeniya KY, Martin CL, Steinfeldt LC, et al. USDA Food and Nutrient Database for Dietary Studies, 5.0. Beltsville: Department of Agriculture, Agricultural Research Service, Food Surveys Research Group; 2012.
18.
Zurück zum Zitat Guenther PM, Casavale KO, Reedy J, Kirkpatrick SI, Hiza HA, Kuczynski KJ, et al. Update of the Healthy Eating Index: HEI-2010. J Acad Nutr Diet. 2013;113:569–80.CrossRef Guenther PM, Casavale KO, Reedy J, Kirkpatrick SI, Hiza HA, Kuczynski KJ, et al. Update of the Healthy Eating Index: HEI-2010. J Acad Nutr Diet. 2013;113:569–80.CrossRef
20.
Zurück zum Zitat Centers of Disease Control and Prevention. 2000 CDC growth charts for the United States: methods and development. Vital Health Stat. 2002;11:246. Centers of Disease Control and Prevention. 2000 CDC growth charts for the United States: methods and development. Vital Health Stat. 2002;11:246.
21.
Zurück zum Zitat National Cholesterol Education Program: National heart, lung, and blood institute. National institutes of health. Detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel III); 2002. NIH Publication No. 02–5215. National Cholesterol Education Program: National heart, lung, and blood institute. National institutes of health. Detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel III); 2002. NIH Publication No. 02–5215.
22.
Zurück zum Zitat Hiza HA, Casavale KO, Guenther PM, Davis CA. Diet quality of Americans differs by age, sex, race/ethnicity, income, and education level. J Acad Nutr Diet. 2013;113:297–306.CrossRef Hiza HA, Casavale KO, Guenther PM, Davis CA. Diet quality of Americans differs by age, sex, race/ethnicity, income, and education level. J Acad Nutr Diet. 2013;113:297–306.CrossRef
23.
Zurück zum Zitat Reedy J, Krebs-Smith SM, Bosire C. Evaluating the food environment: application of the Healthy Eating Index-2005. Am J Prev Med. 2010;38:465–71.CrossRef Reedy J, Krebs-Smith SM, Bosire C. Evaluating the food environment: application of the Healthy Eating Index-2005. Am J Prev Med. 2010;38:465–71.CrossRef
24.
Zurück zum Zitat Juan WY, Guenther PM, Kott PS. Nutrition Insight 41. Alexandria: United States Department of Agriculture Center for Nutrition Policy and Promotion; 2008. Diet quality of older Americans in 1994–96 and 2001–02 as measured by the Healthy Eating Index-2005. Juan WY, Guenther PM, Kott PS. Nutrition Insight 41. Alexandria: United States Department of Agriculture Center for Nutrition Policy and Promotion; 2008. Diet quality of older Americans in 1994–96 and 2001–02 as measured by the Healthy Eating Index-2005.
25.
Zurück zum Zitat Fulgoni VL, Keast DR, Drewnowski A. Development and validation of the Nutrient-rich Foods Index: a tool to measure nutritional quality of foods. J Nutr. 2009;139:1549–54.CrossRef Fulgoni VL, Keast DR, Drewnowski A. Development and validation of the Nutrient-rich Foods Index: a tool to measure nutritional quality of foods. J Nutr. 2009;139:1549–54.CrossRef
26.
Zurück zum Zitat Nicklas TA, O'Neil CE, Fulgoni VL. Diet quality is inversely related to cardiovascular risk factors in adults. J Nutr. 2012;142:2112–8.CrossRef Nicklas TA, O'Neil CE, Fulgoni VL. Diet quality is inversely related to cardiovascular risk factors in adults. J Nutr. 2012;142:2112–8.CrossRef
27.
Zurück zum Zitat Chiuve S, Fung T, Rimm E, Hu F, McCullough M, Wang M, et al. Alternative dietary indices both strongly predict risk of chronic disease. J Nutr. 2012;142:1009–18.CrossRef Chiuve S, Fung T, Rimm E, Hu F, McCullough M, Wang M, et al. Alternative dietary indices both strongly predict risk of chronic disease. J Nutr. 2012;142:1009–18.CrossRef
28.
Zurück zum Zitat Reedy J, Mitrou PN, Krebs-Smith SM, Wirfält E, Flood A, Kipnis V, et al. Index-based dietary patterns and risk of colorectal cancer: the NIH-AARP Diet and Health Study. Am J Epidemiol. 2008;168:38–48.CrossRef Reedy J, Mitrou PN, Krebs-Smith SM, Wirfält E, Flood A, Kipnis V, et al. Index-based dietary patterns and risk of colorectal cancer: the NIH-AARP Diet and Health Study. Am J Epidemiol. 2008;168:38–48.CrossRef
29.
Zurück zum Zitat O'Neil CE, Nicklas TA, Rampersaud GC, Fulgoni VL. One hundred percent orange juice consumption is associated with better diet quality, improved nutrient adequacy, and no increased risk for overweight/obesity in children. Nutr Res. 2011;31:673–82.CrossRef O'Neil CE, Nicklas TA, Rampersaud GC, Fulgoni VL. One hundred percent orange juice consumption is associated with better diet quality, improved nutrient adequacy, and no increased risk for overweight/obesity in children. Nutr Res. 2011;31:673–82.CrossRef
30.
Zurück zum Zitat Bouvard V, Loomis D, Guyton KZ, Grosse Y, Ghissassi FE, Benbrahim-Tallaa L, et al. Carcinogenicity of consumption of red and processed meat. Lancet Oncol. 2015. doi:10.1016/S1470-2045(15)00444-1. Bouvard V, Loomis D, Guyton KZ, Grosse Y, Ghissassi FE, Benbrahim-Tallaa L, et al. Carcinogenicity of consumption of red and processed meat. Lancet Oncol. 2015. doi:10.​1016/​S1470-2045(15)00444-1.
32.
Zurück zum Zitat van Dam RM, Willett WC, Rimm EB, Stampfer MJ, Hu FB. Dietary fat and meat intake in relation to risk of type 2 diabetes in men. Diabetes Care. 2002;25:417–24.CrossRef van Dam RM, Willett WC, Rimm EB, Stampfer MJ, Hu FB. Dietary fat and meat intake in relation to risk of type 2 diabetes in men. Diabetes Care. 2002;25:417–24.CrossRef
33.
Zurück zum Zitat Micha R, Wallace SK, Mozaffarian D. Red and processed meat consumption and risk of incident coronary heart disease, stroke, and diabetes mellitus: A systematic review and meta-analysis. Circulation. 2010;121:2271–83.CrossRef Micha R, Wallace SK, Mozaffarian D. Red and processed meat consumption and risk of incident coronary heart disease, stroke, and diabetes mellitus: A systematic review and meta-analysis. Circulation. 2010;121:2271–83.CrossRef
34.
Zurück zum Zitat Rohrmann R, Overvad K, Bueno-de-Mesquita HB, Jakobsen MU, Egeberg R, Tjønneland A, et al. Meat consumption and mortality - results from the European Prospective Investigation into Cancer and Nutrition. BMC Med. 2013;11:63. doi:10.1186/1741-7015-11-63.CrossRef Rohrmann R, Overvad K, Bueno-de-Mesquita HB, Jakobsen MU, Egeberg R, Tjønneland A, et al. Meat consumption and mortality - results from the European Prospective Investigation into Cancer and Nutrition. BMC Med. 2013;11:63. doi:10.​1186/​1741-7015-11-63.CrossRef
Metadaten
Titel
Association of lunch meat consumption with nutrient intake, diet quality and health risk factors in U.S. children and adults: NHANES 2007–2010
verfasst von
Sanjiv Agarwal
Victor L. Fulgoni III
Eric P. Berg
Publikationsdatum
01.12.2015
Verlag
BioMed Central
Erschienen in
Nutrition Journal / Ausgabe 1/2015
Elektronische ISSN: 1475-2891
DOI
https://doi.org/10.1186/s12937-015-0118-9

Weitere Artikel der Ausgabe 1/2015

Nutrition Journal 1/2015 Zur Ausgabe

Leitlinien kompakt für die Innere Medizin

Mit medbee Pocketcards sicher entscheiden.

Seit 2022 gehört die medbee GmbH zum Springer Medizin Verlag

Erhebliches Risiko für Kehlkopfkrebs bei mäßiger Dysplasie

29.05.2024 Larynxkarzinom Nachrichten

Fast ein Viertel der Personen mit mäßig dysplastischen Stimmlippenläsionen entwickelt einen Kehlkopftumor. Solche Personen benötigen daher eine besonders enge ärztliche Überwachung.

Nach Herzinfarkt mit Typ-1-Diabetes schlechtere Karten als mit Typ 2?

29.05.2024 Herzinfarkt Nachrichten

Bei Menschen mit Typ-2-Diabetes sind die Chancen, einen Myokardinfarkt zu überleben, in den letzten 15 Jahren deutlich gestiegen – nicht jedoch bei Betroffenen mit Typ 1.

15% bedauern gewählte Blasenkrebs-Therapie

29.05.2024 Urothelkarzinom Nachrichten

Ob Patienten und Patientinnen mit neu diagnostiziertem Blasenkrebs ein Jahr später Bedauern über die Therapieentscheidung empfinden, wird einer Studie aus England zufolge von der Radikalität und dem Erfolg des Eingriffs beeinflusst.

Costims – das nächste heiße Ding in der Krebstherapie?

28.05.2024 Onkologische Immuntherapie Nachrichten

„Kalte“ Tumoren werden heiß – CD28-kostimulatorische Antikörper sollen dies ermöglichen. Am besten könnten diese in Kombination mit BiTEs und Checkpointhemmern wirken. Erste klinische Studien laufen bereits.

Update Innere Medizin

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.