ASSESSING THE PERFORMANCE OF WOMEN ON NUTRITION LABELING TASKS.

Abstract: This study evaluated the ability of women (N=150), aged 25 to 45, to locate and manipulate Nutrition Facts label data and assess nutrient content and health claim accuracy. Participants report reading labels regularly and that labels strongly influenced their food purchasing choices. Participants could skillfully locate and manipulate label data and assess nutrient content claim accuracy. They were least skillful at assessing health claims. For Nutrition Facts labels to have the greatest impact on food purchasing decisions and generate expected health care savings and productivity increases, education continues to be key. The findings provide insight into directions that labeling education should take.

The Nutrition Labeling and Education Act of 1990 (NLEA) brought sweeping changes to the U.S. marketplace-it placed standardized nutrient information about food and its place in a healthful diet in consumers' hands (Kurtzweil, 1993). Specifically, the NLEA overhauled nutrition labels on food packages, expanded the scope of nutrition labeling, explicitly defined nutrient content claims, and limited health claims on food packaging to those approved by the Food and Drug Administration (Kurtzweil, 1993; Levy & Derby, 1996). The $2 billion spent by the U.S. food industry to implement the new NLEA regulations is expected to result in a $4 billion to $100 billion savings over the next two decades in health care cost savings and related improvements in productivity (Silverglade, 1997).

A goal of the NLEA was to educate consumers about how they can use nutrition information on food labels to maintain health (Derby & Fein, 1995). U.S. consumers identify food labels as their most frequently used source of nutrition information (Bender & Derby, 1992; Guthrie, Fox, Cleveland, & Welsh, 1995). The rate at which Americans report using nutrition labels nearly reaches the 85 percent goal set by Healthy People 2000 objectives (American Dietetic Association, 1997; Kreuter, Brennan, Scharff, & Lukawago, 1997; Neuhouser, Kristal, & Patterson, 1999; U.S. Department of Health and Human Services, 1991). While several studies have investigated the frequency with which consumers use nutrition labels, few studies have examined consumers' ability to use labels to perform various tasks. Even less research has been conducted to examine consumers' ability to judge the accuracy of nutrient content and health claims that appear on food packages (Keystone Center, 1996). To reap the predicted health care and productivity cost savings, consumers must be willing and able to use nutrition labels.

Adult women of child-bearing years represent an appropriate consumer group to study because, currently, 80 to 85 percent of all women in the U.S. bear the primary responsibility for food purchasing and preparation (International Food Information Center, 1999). Females, thus, are their families' food gatekeepers. Because women have such a large share of the responsibility for their families' food availability, their ability to use the nutrition information on food packages can impact two or more generations and may be the key to the development of eating patterns that will help future generations reduce their risk of chronic diet-related diseases. Thus, the purpose of this study was to evaluate the abilities of women to locate and manipulate information on Nutrition Facts labels and determine their ability to assess the accuracy of nutrient content and health claims.

METHODOLOGY SAMPLE

The sample for this study was limited to women (N=150) between the ages of 25 and 45 years who served as their households' primary food purchasers (i.e., they were responsible for half or more of the household food shopping). In order to investigate any effect the presence of children in the household might have on Nutrition Facts label use and knowledge, half of the study sample had no children under the age of 18 living with them for any portion of time. The other half had children under the age of 18 present in their households at least 50 percent of the time each week. Women excluded from this study were those employed in a health or nutrition-related job or had a spouse or partner working in these areas because they likely had a greater interest in and knowledge of nutrition and health than other women. Women who had visual impairments that made it impossible to read food labels also were excluded. Participants in this quota controlled convenience sample were recruited by the researchers from local community groups.

INSTRUMENT

The study instrument was designed to be administered in a 15-minute, face-to-face interview and was based on instruments used in previously reported research (Byrd-Bredbenner, 1994; Levy & Fein, 1998; Levy, Fein, & Schucker, 1996; Lewis & Yetley, 1992). The instrument was reviewed by a panel of nutrition and/or tests and measurements experts (n=6) for intended purpose, ambiguity, and usefulness in order to establish content validity. The experts' input was used to revise the instrument. Next, the instrument was pilot tested (n=6) with women having characteristics similar to the study's sample. Pilot test results were used to refine the instrument.

The study instrument had three main sections. Section 1 served to acquaint the participants with the purpose of the study and their role. It also was designed to insure that the individual matched the study sample eligibility requirements. Section 2 collected demographic data and asked participants to self-assess their diet quality and health status (i.e., excellent, good, fair, or poor) as well as the degree to which they believed they were informed about nutrition (i.e., very, somewhat, or not informed). Section 2 also collected data regarding nutrition label usage behaviors including frequency labels are read, frequency with which labels impact food purchases, and stage of change for reading nutrition labels the first time a food is purchased (Prochaska, Norcross, & DiClemente, 1994; Prochaska & Velicer, 1997). Women who were not presently reading nutrition labels when buying new food items were placed in the pre-action stage of change (i.e., in the precontemplation, contemplation, or preparation stage) whereas those who were reading labels before buying a food the first time were placed in the action/maintenance stage of change. The basic premise of the Stage of Change model is that behavior change is a dynamic process--when people change a behavior, they move through a virtually universal series of sequential and predictable stages of change. By knowing which stage a client is in for a particular behavior, health professionals can select the instructional methods that are most appropriate to the client's stage (Prochaska, et al., 1994).

Section 3 contained four label reading knowledge scales. Scale A-Ability to Locate Quantitative Information on the Label (abbreviated Scale A-Locate) appraised participants' skill at accurately locating and retrieving nutrition label information. Study participants were instructed to use a Nutrition Facts label to answer five questions like these: How much total carbohydrate is in one serving of this food? How much saturated fat is in one serving of this food? Each correct answer earned one point. Total points accrued equal the score for Scale A-Locate; thus scores for this scale could range from 0 to 5. Higher scores indicate a greater ability to accurately locate and retrieve label information. The Kuder-Richardson 20 reliability coefficient for Scale A-Locate was 0.99.S

Scale B-Ability to Manipulate Quantitative Information on the Label (abbreviated Scale B-Manipulate) was designed to assess ability to make simple diet planning calculations. Participants were asked to use a second Nutrition Facts label to answer five questions like these: How many servings of this food would you need to eat to get all the calcium you need in a day? If you ate two servings of this food, how much fiber would you get? The score for Scale B-Manipulate was computed using the procedure described above for Scale A-Locate. Scores could range from 0 to 5 with higher scores reflecting a greater skill al manipulating label information. For Scale B-Manipulate, the Kuder-Richardson 20 reliability coefficient was 0.88.

Scale C-Ability to Judge Nutrient Content Claim Truthfulness (abbreviated Scale C-Nutrient Content Claims) evaluated the participants' ability to use a Nutrition Facts label to judge the truthfulness of nutrient content claims. This scale had two parts and was modeled closely on previously reported research (Levy & Fein, 1998; Levy, Fein, & Schucker, 1991; Levy, Fein, & Schucker, 1996). The first part of this scale instructed participants to rate the healthfulness of a food on a scale of 1 to 10 (1 = not healthful at all and 10 = very healthful) using only the food's name. Participants then were presented with a list of four nutrient content claims that were made about the food. They were asked once again to rate the healthfulness of the food using the same 10-point scale. Finally, participants were shown a Nutrition Facts label for the food and instructed once more to rate the healthfulness of the food on the 10-point scale. This exercise was repeated twice using two different foods (i.e., condensed soup and macaroni and cheese). The first healthfulness rating gathered baseline perceptions about the food's healthfulness. A panel of nutrition and health experts all agreed that the nutrient content claims assigned to each food item were positive attributes (e.g., high in vitamin A, sodium free, and zero sugar) and that the claims should raise perceptions of the food's healthfulness. The Nutrition Facts label was provided to ascertain whether participants used it to judge the nutrient content claims' truthfulness. Two of the claims for each food item were factually false. Thus, if the participant used the Nutrition Facts label to judge the claims' truthfulness, their healthfulness rating should decrease. The impact of the Nutrition Facts label on the participants' product evaluations represents "a practically important use of the food label related to product preference and purchase probability" (Levy, Fein, & Schucker, 1996). In order to confirm that this scale functioned as intended, a nutrition expert panel was asked to complete this portion of the instrument. As expected, the panels' ratings increased from baseline after seeing the nutrient content claims and decreased after seeing the Nutrition Facts label.

The second part of Scale C-Nutrient Content Claims sought to measure participants' ability to judge the truthfulness of each of the eight nutrient content claims (i.e., factually correct or incorrect) they were shown in part one of Scale C-Nutrient Content Claims. A score for part two of this scale was computed by awarding one point for each correctly judged claim. Scale scores could range from 0 to 8 with higher scores reflecting a greater ability to judge nutrient content claim truthfulness. The Kuder-Richardson 20 reliability coefficient for the second part of Scale C-Nutrient Content Claims was 0.72.

Scale D-Ability to judge health claim accuracy (abbreviated Scale D-Health Claims) measured participants' ability to judge whether a pasta mix bearing the Nutrition Facts label they were given could bear each of five health claims. The health claims used in this scale all are permitted to appear on food packages provided the food meets the Food and Drug Administration's (FDA) requirements for that health claim. Three of the five health claims used on this scale met the FDA requirements and would be legally permitted on the pasta mix. The remaining two health claims did not meet the FDA requirements and, thus would not be permitted to appear on the pasta mix. One point was awarded for each correct answer; thus the total scale score could range from 0 to 5. Higher scores on this scale indicate a greater ability to accurately judge whether a health claim would or would not be permitted to appear on a food's package. The Kuder-Richardson 20 reliability coefficient for Scale D-Health Claims was 0.58.

RESULTS AND DISCUSSION SAMPLE

The mean age of the study participants was 34.6 [+ or -] 6.1 standard deviation (SD). Nearly 60 percent (n=86) were college graduates, one-quarter had received some post secondary education, and 17 percent (n=26) had only a high school or less education. Socioeconomic status (SES), determined using a census-based occupational prestige scale (Stevens & Cho, 1985), was moderate (i.e., 7.4 [+ or -] 3.1SD) on a scale of 1 (high) to 14 (low). Most study participants' self-assessment of the overall quality of their diets was good or excellent and their health status self-assessment was good to excellent (82% and 89%, respectively). In addition, the majority (85%) believed that they were somewhat or very informed about nutrition. Nine out of 10 participants reported that they never received any type of instruction (including print media, classroom instruction, consultation with a health professional) regarding the use of nutrition labels. There was no significant difference in mean age, education level, SES, receipt of labeling reading instruction, or perceived quality of diet, health status, or degree to which they were informed about nutrition between women with and without children in their households.

Over 80 percent (n=122) of the women surveyed indicated that they did all the household food shopping with another 17 percent (n=25) reporting that they did most of the shopping. Only three participants stated that they did only about half the household food shopping. The study participants reported making an average of 1.74 [+ or -] 1.0SD (range 1 to 6) separate trips food shopping weekly and spent an average of 84.4 [+ or -] 40.3SD minutes (range 30 to 240 minutes) food shopping each week. Although women with children and women without children made a similar number of weekly food shopping trips, women with children spent significantly (p [is less than or equal to ] 0.0001; Scheffe F=27.94) more time food shopping (100.4 [+ or -] 45SD minutes vs. 68.4 [+ or -] 27SD minutes) than women without children.

LABEL USAGE BEHAVIOR

An analysis of label reading frequency indicated that 15 percent of the women surveyed reported that they always read Nutrition Facts labels, 61 percent reported reading labels sometimes, and the remainder (23%) indicated that they rarely or never read labels (i.e., they were label non-readers). The percentage of women classified as label readers (i.e., women who always or sometimes read labels) was the same for women with and women without children and is comparable to the rates reported by others (American Dietetic Association, 1997; Kreuter, et al., 1997; Neuhouser, et al., 1999). While it is possible that the surveyed women may have overestimated their rate of label use, there is some older evidence that indicates reported label use corresponds closely to actual label use (Vandenburg, 1981).

While more than three-quarters of the study participants reported reading labels, only 15 percent said they always read them. Although it is not known for certain why this there is such a gap between those who always read labels and those who do so sometimes, this gap may have occurred because individuals repeat meal patterns and thus, theoretically, only need to read a label one time (Kreuter, et al., 1997). In another study (Miller, Probart, & Achterberg, 1997), women reported reading labels when they purchased a food for the first time, but rarely read them on subsequent purchases due to time constraints. These may be plausible explanations for the gap noted above considering the fact that over 91 percent of the women surveyed were in the action/maintenance stage of change for reading nutrition labels the first time a food is purchased (i.e., they regularly read nutrition labels when purchasing a food for the first time). The percentage of surveyed women regularly reading labels when purchasing a new food is quite similar to the rates reported by other researchers (Govindasamy & Italia, 1999; Marietta, Welshimer, & Anderson, 1999; Miller, et al., 1997).

Not only did the survey participants report reading labels regularly, they indicated that labels had a strong impact on their food purchasing choices. Specifically, over 91 percent of the surveyed women stated that Nutrition Facts labels always or sometimes affected their food purchasing decisions. This rate is higher than reported by other researchers. For example, less than half the female patients at family medicine clinics reported that nutrition labels influence most or all of their food purchasing decisions (Kreuter, et al., 1997).

LABEL READING KNOWLEDGE

Scale A-Locate. The mean score on this scale was 4.97 [+ or -] 0.4SD. The maximum possible score was 5, thus it can be concluded that the study participants were highly skilled at locating and retrieving data from a Nutrition Facts label. Considering that the overwhelming majority of study participants had never received any type of instruction regarding nutrition labeling, these data appear to indicate that the design of the Nutrition Facts label is easy to read.

A review of Table 1 reveals that significant differences existed among those with varying self-assessment of their diet quality, health status, and degree of being informed about nutrition. The better the self-assessment, the higher the score of Scale A-Locate tended to be. The finding that performance on this scale did not differ significantly with the frequency with which the participant read nutrition labels supports previous research (Levy & Fein, 1998). This finding further supports the notion that the Nutrition Facts label is easy to read in that those with less experience using it scored similarly on this scale to those with more experience.

[TABULAR DATA 1 NOT REPRODUCIBLE IN ASCII]

Scale B-Manipulate. The mean score for this scale was 4.66 [+ or -] 0.6SD, which indicates that the participants were able to skillfully manipulate nutrition label data despite a lack of nutrition labeling instruction. Performance on Scale B-Manipulate appears to further indicate that the Nutrition Facts label design is easy to read. Additionally, it is a consumer-friendly tool that can be skillfully used for simple diet planning tasks. However, performance on Scale B-Manipulate did improve significantly as educational level rose. In contrast to previously reported research (Levy & Fein, 1998), those who frequently read nutrition labels (i.e., label readers) performed significantly better on this scale than non-readers.

The overall skilled performance on this scale contrasts with recently published studies which reported that consumers frequently were unable to make accurate mathematical calculations based on food labels (Levy & Fein, 1998; Miller et al., 1998). Findings from one study (Levy & Fein, 1998) likely differed because the investigation was conducted prior to the selection of the final Nutrition Facts label format, which includes percent Daily Value (DV). The DV eliminates the need for consumers to perform computations to relate the amount of a nutrient in a food to the recommended daily intake; thus the DV may have enhanced performance on this scale. The findings from the second study (Miller, et al., 1997) likely differed because the women surveyed tended to be older (i.e., 40 to 60) than this study's participants. Others have reported that younger people tend to perform better on nutrition labeling tasks than older persons (Cole & Balasubramanian, 1993; Cole & Gaeth, 1990; Levy & Fein, 1998; Moorman, 1990).

Scale C-Nutrient Content Claims. Analysis of variance and follow-up procedures of the first part of Scale C-Nutrient Content Claims indicated that participants' healthfulness rating of both foods rose significantly from baseline after participants were shown the nutrient content claims (see Table 2). After being shown the Nutrition Facts label, the healthfulness ratings dropped significantly. The significant differences between the baseline and being shown nutrient content claims and between seeing the nutrient content claims and the Nutrition Facts label indicate the impact of nutrient content claims and Nutrition Facts labels on participants' product evaluations (Levy, et al., 1996). The data indicate that the nutrient content claims affected the surveyed women's perceptions of the foods and that the women accurately read the Nutrition Facts labels to discern the truthfulness of the nutrient content claims. These findings are comparable to those reported previously (Levy, et al., 1996).

Table 2. Part One of Scale C-Nutrient Content Claims: Healthfulness Ratings

                       Condensed Soup Mean     Macaroni & Cheese
Healthfulness Rating   [+ or -] SD(#)          Mean [+ or -] SD(#)

Baseline Rating
                       4.7 [+ or -] 1.9a(*)    6.0 [+ or -] 1.6(c)
Rating after being
  shown nutrient
  content claims
                       7.0 [+ or -] 2.1(ab)    8.0 [+ or -] 1.7(cd)
Rating after being
  shown Nutrition
  Facts label
                       5.4 [+ or -] 2.00(b)    6.4 [+ or -] 1.8(d)

(#) Scores can range from 1 (not healthful at all) to 10 (very healthful).

(*) Values followed by the same superscript are significantly different.

(a) p [is less than or equal to] 0.0001, Scheffe F = 211.03; (b) p [is less than or equal to] 0.0001, Scheffe F = 106.28; (c) p [is less than or equal to] 0.0001, Scheffe F = 208.32; (d) p [is less than or equal to] 0.0001, Scheffe F = 137.6.

The mean score for the second part of Scale C-Nutrient Content Claims (see Table 1) indicates that study participants were able to judge the truthfulness of the nutrient content claims 82 percent of the time. This accuracy rate exceeds the rate reported by others (Levy & Fein, 1998). This difference may be due to the fact that earlier research did not use the current Nutrition Facts label format. As was seen in Scale A-Locate, significant differences existed in Scale C-Nutrient Content Claims between those with varying self-assessments of their diet quality.

Scale D-Health Claims. Table 1 shows that of all the label reading knowledge scales, participants performed most poorly on Scale D-Health Claims. The mean score indicates that participants were able to accurately state whether a health claim would be permitted on a food only 60 percent of the time-performing only slightly better than chance. Although it is not possible to determine why participants performed poorly on this scale, the reason may be related to the high level of skepticism and mistrust of health claims on product packages that have been reported by others (Keystone Center, 1996; Levy, 1995; Miller, et al., 1997). That is, many view claims as advertising ploys and have little faith in them (Anonymous, 1997). Plus, consumers do not understand health claims (Keystone Center, 1996) and may be unaware that health claims on products help fulfill a public health information function (Anonymous, 1997). Health claims also are the hardest for consumers to validate because, unlike nutrient content claims, there are no `concrete' data on the label that allow consumers to verify the accuracy of health claims (McNutt, 1997). Consumer perceptions, lack of knowledge, and the very nature of health claims themselves may impair the ability of health claims to communicate believable, useful health information about a food product and diminish their ability to fulfill a public health information function (Anonymous, 1997; Keystone Center, 1996; Levy, Derby, & Roe, 1997).

CONCLUSION

"One of the most valuable real estate locations in the food marketing environment is the food label-a very hot property. Consumers face more than 30,000 items in a supermarket and 34 new product launchings every day. Their eyes linger a mere 2.5 second on each product during an average shopping trip. The challenge for health educators and food marketers is to determine and evaluate what information helps consumers decide-in the blink of an eye-which products will move off the shelves and into their carts" (Coulston, p. 1470).

There's no doubt that the information on the food label can assist in the decision making process. For Nutrition Facts labels to have the greatest impact on food purchasing decisions and generate the expected health care savings and productivity increases, consumers need to be able to skillfully use the information available. Education continues to be key. The findings of this investigation provide some insight into directions that labeling education should take. For example, this study indicates that consumers are aware of Nutrition Facts labels and that such labels are designed in a manner that allows consumers to quickly and easily locate and retrieve information. Thus, labeling education programs likely do not need to emphasize raising consumer awareness. Another finding is that, overall, the women in this study were able to skillfully manipulate labeling data to complete dietary planning tasks, although those with higher education levels did perform better. The impact of education level as well as data indicating that many consumers do not use the DV (Neuhouser, et al., 1999) and/or have difficulty with computations associated with using the DV in meal planning (Guthrie, et al., 1995; Levy & Fein, 1998; Levy, Patterson, Kristal, & Li, 2000; Neuhouser, et al., 1999) indicate that nutrition labeling instruction needs to focus more on the DV (Guthrie, et al., 1995; Neuhouser, et al., 1999). In addition, to facilitate the use of DV, it may be important to emphasize that the nutrient values on the label are for one serving of the size indicated (Miller, et al., 1997).

Making educational opportunities responsive to personal needs may help consumers to more quickly gain needed skills. Labeling education can be personalized by teaching consumers who have diets containing more or less than 2000 calories how to easily adjust the DV (Miller, et al., 1997). For those with a diet-related health condition, emphasizing nutrients relevant to the their personal medical history is important (Kreuter, et al., 1997; Miller, et al., 1997). Researchers have reported that patients with hypertension were more likely to review sodium values and those with elevated blood cholesterol levels were more likely to examine cholesterol or saturated fat values than others without these health conditions (Kreuter, et al., 1997).

The relationship between education level and ability to manipulate labeling data noted in this study (see Table 1) suggests the need for educational materials that are targeted to those with a high school or less education. Because educational level achieved tends to be positively correlated with literacy level, these materials likely need to be at a literacy level lower than typically seen in nutrition and labeling education materials (Brunt & Schafer, 1997; Dollahite, Thompson, & McNew, 1996). The need for lower literacy labeling education materials is underscored by the fact that more than 20 percent of the adults in the U.S. have severely limited reading skills and another 25 percent or more are functionally illiterate (U.S. Department of Education, 1993). Thus, labeling education pamphlets written for low literacy consumers have the potential to increase the knowledge and skill of significant numbers of U.S. adults (Brunt & Schafer, 1997). Concomitantly, labeling education materials for lower literacy audiences could enhance the fulfillment of the NLEA's education objective.

Although participants in this study seemed to have fairly good knowledge of nutrient content claims, their knowledge of health claims was clearly lacking. The skepticism associated with nutrient content and health claims (Cronin, Achterberg, & Sims, 1993; Derby & Fein, 1995; Miller, et al., 1997), consumer misperceptions, and lack of knowledge about claims represents a major opportunity for health educators to design programs that effectively communicate health messages using nutrient content and health claims on labels (McMahon, 1995). Consumers need to know with certainty that nutrient content and health claims are tightly regulated (Miller, et al., 1997). They also need opportunities to explore how they can use claims to find foods with the nutrition characteristics they desire. Consumers have reported that grocery shopping is hard work and time consuming (Miller, et al., 1997), that time constraints are a major barrier to reading labels while grocery shopping, and that the majority of food purchasing decisions are made at the grocery store (Light, Portnoy, Blair, Smith, Rodgers, Tuckermanty, Tenney, & Mathews, 1989). These reports indicate that one way to get consumers to use claims might be to focus on the fact that claims can be read quickly and thus, lighten the time and energy burden associated with food shopping.

While the findings of this investigation have contributed to our understanding of women's nutrition labeling skill and usage rates, the study has several limitations. First, analyses are based on cross-sectional data collected from women in one northeastern state. Thus, the data likely cannot be generalized to other women living in other regions. However, the percentage of women who report reading labels is congruent with published data (American Dietetic Association, 1997; Kreuter, et al., 1997, Neuhouser, 1999) and the label usage rates for study participants is reflective of the rates reported for women, consumers in the age group studied, consumers in the northeastern U.S., and those at each educational level (Bender & Derby, 1992). Because the study participants were recruited and agreed to be interviewed and the data are based on self-report, social desirability bias cannot be ruled out. Another potential limitation is that the interviews were conducted in a relatively distraction-free room which is not similar to the often chaotic and noisy atmosphere of most grocery stores where nutrition label reading activities commonly occur.

There's little doubt that the information on food labels can help consumers make sound dietary choices in accordance with the Dietary Guidelines for Americans (U.S. Department of Agriculture and U.S. Department of Health and Human Services, 1995). However, education continues to be vital--the usefulness of the sweeping changes brought about by the NLEA and the potential for nutrition labeling to improve the health of Americans may be diminished unless consumers are taught how to use the information that has been placed at their fingertips (Kurtzweil, 1993; Morreale & Schwartz, 1995). Labeling education programs that are responsive to consumer needs and interests continue to be necessary so that nutrition labeling might achieve its public health function.

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Lisa Alfieri, M.A., Montclair State University, 111 Finley Hall, Upper Montclair, NJ 07043, 973655-7489, [e-mail]. Carol Byrd-Bredbenner, Ph.D., R.D., F.A.D.A., Professor and Extension Specialist in Nutrition, Rutgers, The State University of New Jersey, 88 Lipman Drive, New Brunswick, NJ 08901, (PH) 732-932-5000 x604, (FAX) 732-932-6633, [e-mail]. Correspondence to: Carol Byrd-Bredbenner, Ph.D., R.D., F.A.D.A., 4 Ranney Road, Long Valley, NJ 07853, (PH) 732-932-5000 x604, (FAX) 732-932-6633, [e-mail].