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Public Health and Primary Care  |   November 2020
Serum Zinc Concentrations of Adults in an Outpatient Clinic and Risk Factors Associated With Zinc Deficiency
Author Notes
  • From the Department of Primary Care at Heritage College of Osteopathic Medicine at Ohio University in Athens (Drs Gau and Ebersbacher), and the Department of Preventive Medicine and Biometrics at the Uniformed Services University of the Health Sciences in Bethesda, Maryland (Dr Kao). 
  • Preliminary results from this study were orally presented at the 12th International Academy on Nutrition and Aging Annual Meeting at Moscone Center West, San Francisco, California, on July 23, 2017. 
  • Disclaimer: The views expressed in this paper are those of the authors and do not necessarily reflect the official views of the institutions or the United States Department of Defense. 
  • Financial Disclosures: None reported. 
  • Support: This research project was partially funded by NIH grant 5R21DK096201-02 (Gau) and the Research and Scholarly Activity Committee (Ohio University Heritage College of Osteopathic Medicine). 
  •  *Address correspondence to Jen-Tzer Gau, MD, PhD, Ohio University, 355 Grosvenor Hall, 16 W Green Dr, Athens, OH 45701-2974. Email: gau@ohio.edu
     
Article Information
Public Health and Primary Care   |   November 2020
Serum Zinc Concentrations of Adults in an Outpatient Clinic and Risk Factors Associated With Zinc Deficiency
The Journal of the American Osteopathic Association, November 2020, Vol. 120, 796-805. doi:https://doi.org/10.7556/jaoa.2020.138
The Journal of the American Osteopathic Association, November 2020, Vol. 120, 796-805. doi:https://doi.org/10.7556/jaoa.2020.138
Abstract

Context: Subclinical features of zinc deficiency can be challenging to recognize. The prevalence of zinc deficiency based on blood zinc concentration in an adult outpatient clinic setting has not been well-studied.

Objective: To estimate the prevalence of low serum zinc concentrations among community-dwelling adults, and to characterize clinical features and risk factors associated with zinc deficiency.

Methods: This retrospective pilot prevalence study took place from 2014 to 2017 at an outpatient clinic in southeast Ohio. Patients aged 50 years or older with a stable health status were categorized into a case group with zinc deficiency (serum zinc concentration, <0.66 µg/mL) and a control group (serum zinc concentration, ≥0.66 µg/mL). Measurements included serum zinc concentration, nutritional biomarkers (ie, magnesium, calcium, albumin, and total 25-hydroxy vitamin D levels), patient history of fractures and events such as hospitalization, antibiotic use, and self-reported falls that occurred within 1 year prior to the date serum zinc concentration was measured (index date). Patients were excluded if they had a serum zinc measurement within 2 months after a hospitalization, severe renal insufficiency (3 patients with serum creatinine concentration above 2.5 mg/dL), or serum zinc concentration above 1.20 µg/mL.

Results: This study included 157 patients, consisting of a case group of 41 (26%) patients with zinc deficiency and a control group of 116 (74%) without zinc deficiency. Mean (SD) zinc concentrations of the case and control groups were 0.58 (0.05) µg/mL and 0.803 (0.13) µg/mL, respectively (P<.01). Patients in the case group were more likely to have had a history of hospitalization, antibiotic use, a fall within 1 year before the index date, and a history of fractures and hip fracture (P<.01 in each case). Patients taking gastric acid suppressants had increased odds of lower zinc concentrations (odds ratio, 2.24; 95% CI, 1.08-4.63). Both logistic and multivariate linear regression models revealed that past fractures, hip fractures, and hypoalbuminemia (albumin <3.5 g/dL) were associated with zinc deficiency or lower zinc concentrations.

Conclusion: This study revealed that 26% of patients in an outpatient adult clinic had zinc deficiency based on serum concentrations. Patients with fracture history and low serum albumin were at higher risk for zinc deficiency.

Micronutrients play an important role in maintaining good health. Lower serum micronutrient concentrations have been shown to predict frailty during a 3-year follow-up among community residents.1 Micronutrient deficiencies may lead to frailty by disrupting homeostatic mechanisms important for cognition, immunity, and musculoskeletal functioning.1,2 Zinc is a micronutrient that plays an important role in cellular structure and metabolic function.3 An estimated 85% of whole-body zinc (roughly 2.0-2.5 g in average adults) is distributed in muscles (55%) and bones (30%), with 11% in the skin and liver.3 The majority (99.9%) of systemic zinc is located intracellularly, and only a fraction (0.1%) is present in serum.3 Indication of severe zinc deficiency may appear in many organ systems, including skin, gastrointestinal, central nervous, immunity, and skeletal systems.4-5 However, mild zinc deficiency can be less blatant and challenging in routine encounters with health care providers due to the lack of a convenient clinical assessment tool.5-7 Despite this limitation, serum zinc concentration is the main clinical tool to identify zinc deficiency.6-9 
Older adults are particularly vulnerable to zinc deficiency due to low dietary intake10-12 and increasing demand during acute illness, specifically when hospitalized.13 Prevalence of low serum zinc concentrations was reported in more than 8% of a US study population older than 10 years of age using the National Health and Nutrition Examination Survey 2011 to 2014 data.14 Other studies13,15-17 have shown a prevalence of low serum zinc concentrations among older adults who were hospitalized, ranging from 20% to 38%.15,17 One study15 reported that 69% of 51 long-stay geriatric patients (mean age, 85.9 years) had zinc deficiency based on serum zinc concentrations. Globally, it has been estimated that zinc deficiency affects 2 billion people (an estimated 25% of people at risk),4 with as many as 15% to 20% of the global population having insufficient dietary zinc intake.18 
Because it is challenging for clinicians to identify subtle clinical features of zinc deficiency,5,19 the objective of this study was to estimate the prevalence of low serum zinc concentrations among patients at an outpatient clinic. We also aimed to characterize clinical features and determine risk factors associated with lower serum zinc concentrations or zinc deficiency. 
Methods
The institutional review board at Ohio University approved this study; informed consent was not required because of the study's retrospective nature. 
Patients
Study patients were adults aged 50 years or older who had serum zinc concentration measured between January 1, 2014 and May 30, 2017. All patients were community residents who had been well-established with this clinic for at least 1 year and regularly followed up with health care providers (2 physicians and 1 nurse practitioner) in a university-affiliated geriatric clinic in southeast Ohio. Patients were excluded if they had a serum zinc measurement within 2 months after a hospitalization, severe renal insufficiency (serum creatinine concentration above 2.5 mg/dL; 3 patients), or serum zinc concentration above 1.20 µg/mL (patients taking high dose zinc supplements; 3). 
Study Design and Data Collection
This study was case-control in design: the case group included patients with zinc deficiency (serum concentration, < 0.66 µg/mL), and the control group included were patients with normal serum zinc concentration. Because the normal reference range for zinc concentration is 0.66 to 1.10 µg/mL (10.09 to 16.82 µmol/L), the cutoff value for zinc deficiency was set at 0.66 µg/mL. 
Blood samples were obtained for routine blood tests to screen for disorders as allowed by insurance carriers (eg, Medicare Part B) or Medicaid insurance. Blood samples were obtained when patients were at their usual baseline health. Serum zinc measurement was analyzed by dynamic reaction cell-inductively coupled plasma-mass spectrometry (DRC-ICP-MS) performed by Mayo Clinic Laboratory service (Rochester, MN). 
Other nutritional biomarkers, such as vitamin B12, 25-hydroxy vitamin D, and magnesium concentrations, were also collected when available. Red blood cell counts with hemoglobin levels and comprehensive metabolic panels (obtained on or before the index date) were also performed following standard procedures by a hospital-affiliated laboratory service. 
Historical Events
Our study collected data on historical events that occurred within 1 year before the date serum zinc concentration was measured (ie, index date). These events included hospitalization, antibiotic use, self-reported fall, diarrhea, and weight change, which was compared with weight 1 year before the index date. During the 1 year preceding the index date, significant weight loss was defined as loss of at least 10 lbs or more than 10% of baseline weight. History of hip and nonhip fracture was confirmed by documented surgical history. Vertebral or pelvic fracture history was confirmed by radiography reports that were ascertained through the hospital-affiliated radiology department and previous health care providers/facilities if patients were from an outside unaffiliated health care system prior to establishing care with this clinic. 
Data Collection
Patient medical records were retrieved electronically from 2012 forward, as that was the year the electronic medical record system was implemented at this clinic. Data collection also included demographics, smoking status, medical history, and medication use around the index date. Past medical history (eg, diabetes mellitus, hypothyroidism, and depression) were documented as prior events or diagnoses (recorded as ever vs never). All data was recorded on standardized forms. Medical records under study were reviewed and verified by the investigator for accuracy. 
Statistical Analysis
Mean with standard deviation (SD) and percentage were used to report continuous and discrete variables, respectively. χ2 or 2-sample, 2-sided t tests were used to determine whether there was a significant difference between the 2 groups. Univariate logistic regression was used to assess the association between potential risk factors and zinc deficiency. 
To identify factors associated with zinc deficiency, potential confounders were included in the multiple logistic regression model, including age, sex, body mass index (BMI), alcohol use, hip fracture, nonhip fracture, low albumin concentration (cutoff value, <3.5 g/dL), and anemia (Hb<12 g/dL for both genders). Adjusted odds ratios (OR) with 95% confidence intervals (CI) were estimated. Those variables were also included in multiple linear regression models for serum zinc concentrations among our study patients. Results remained similar when serum albumin and blood hemoglobin concentrations were analyzed as continuous variables in the above models. Regression coefficients with 95% CI were estimated. 
Regression diagnostics revealed that our multivariable models were reasonable, and there was no collinearity among the models’ independent variables. Statistical significance level (type I error rate) was set at a level of .05. PC SAS version 9.3 software (SAS Institute, Inc.) was used to perform the statistical analyses. 
Results
Characteristics of Cases (Zinc-Deficiency) and Controls
In this study, a total of 157 patients were included, with an age range of 52 to 97 years. We found that 41 adult patients (26%) had zinc deficiency. Both case and control groups were similar regarding BMI, alcohol use, smoking status, and comorbidities, although the mean (SD) age of the case group was older than the mean (SD) age of the control group (82.6 [8.7] vs. 78.2 [8.9] years; P=.007). 
The case group had more events than the control group within 1 year prior to the index date, including hospitalizations (18 [44%] vs 18 [16%]), antibiotic use (26 [63%] vs 46 [40%]), and self-reported fall (23 [56%] vs 14 [12%], Table 1). Self-reported diarrhea within 3 months prior to the index date was also more frequent among cases than controls (6 [15%] vs 5 [4%], Table 1). Furthermore, cases were more likely to have reported ever event(s) than controls for any fracture (22 [54%] vs 9 [8%]), hip fracture (7 [17%] vs 3 [3%]), nonhip fracture (15 [37%] vs 7 [6%]), and vertebral fracture (7 [17% ] vs 1 [1%]). 
Table 1.
Characteristics of Zinc Deficiency and Controls Among Adults at an Adult Clinic in Southeast Ohioa (N=157)
Variablesb Zinc deficiency case group (n=41) Control group (n=116) P value
Demographics
 Age, mean (SD) 82.6 (8.7) 78.2 (8.9) .007
 White 40 (98) 100 (86) .044
 Women 29 (71) 73 (63) .368
 Weight, lb (SD) 161.3 (42.1) 163.4 (38.6) .769
 Body mass index (SD) 28.6 (6.7) 27.9 (5.4) .479
 Alcohol use regularly 8 (20) 16 (14) .382
 Current smoker 5 (12) 11 (10) .622
 Past smoking history 17 (42) 51 (44) .781
Associated comorbidity
 Diabetes mellitus 10 (24) 22 (19) .459
 Hypothyroidism 9 (22) 27 (23) .862
 Gastroesophageal reflux disease 24 (59) 57 (49) .301
 Depression 23 (56) 56 (48) .389
Events in the past 1 year
 Hospitalization 18 (44) 18 (16) <.001
 Use of antibiotics 26 (63) 46 (40) .009
 Fall 23 (56) 14 (12) <.001
 Significant weight lossc 10 (25) 18 (16) .178
 Diarrhea (reported in past 3 months) 6 (15) 5 (4) .026
History of fractures
 All fracture 22 (54) 9 (8) <.001
 Hip fracture 7 (17) 3 (3) .0034d
 Nonhip fracture 15 (37) 7 (6) <.001
 Vertebral fracture (radiographically confirmed) 7 (17) 1 (1) <.001
Medication use
 Zinc supplements 0 (0) 12 (10) .037d
 Iron supplements 5 (12) 7 (6) .202
 Magnesium supplements 16 (39) 26 (22)
 Vitamin D supplements 31 (76) 97 (84) .256
 Calcium supplements 15 (37) 37 (32) .584
 Proton pump inhibitors 21 (51) 37 (32) .028
 H2 receptor antagonists 3 (7) 5 (4) .431d
 Gastric acid suppressants 23 (56) 41 (35) .020
 Diuretics 15 (37) 37 (32) .584
 Antihypertensive 28 (68) 76 (66) .747
 Antibiotics 25 (61) 42 (36) .006
 Narcotic drugs 15 (37) 24 (21) .043

a Zinc deficiency was defined as serum zinc concentration less than 0.66 mcg/mL (normal range, 0.66 to 1.10).

b Data given as No. (%) unless otherwise noted.

c Significant weight loss was defined as weight loss >10% or >10 lb loss compared with 1 year prior.

d P values were estimated by Fisher exact test.

Abbreviation: SD, standard deviation.

Table 1.
Characteristics of Zinc Deficiency and Controls Among Adults at an Adult Clinic in Southeast Ohioa (N=157)
Variablesb Zinc deficiency case group (n=41) Control group (n=116) P value
Demographics
 Age, mean (SD) 82.6 (8.7) 78.2 (8.9) .007
 White 40 (98) 100 (86) .044
 Women 29 (71) 73 (63) .368
 Weight, lb (SD) 161.3 (42.1) 163.4 (38.6) .769
 Body mass index (SD) 28.6 (6.7) 27.9 (5.4) .479
 Alcohol use regularly 8 (20) 16 (14) .382
 Current smoker 5 (12) 11 (10) .622
 Past smoking history 17 (42) 51 (44) .781
Associated comorbidity
 Diabetes mellitus 10 (24) 22 (19) .459
 Hypothyroidism 9 (22) 27 (23) .862
 Gastroesophageal reflux disease 24 (59) 57 (49) .301
 Depression 23 (56) 56 (48) .389
Events in the past 1 year
 Hospitalization 18 (44) 18 (16) <.001
 Use of antibiotics 26 (63) 46 (40) .009
 Fall 23 (56) 14 (12) <.001
 Significant weight lossc 10 (25) 18 (16) .178
 Diarrhea (reported in past 3 months) 6 (15) 5 (4) .026
History of fractures
 All fracture 22 (54) 9 (8) <.001
 Hip fracture 7 (17) 3 (3) .0034d
 Nonhip fracture 15 (37) 7 (6) <.001
 Vertebral fracture (radiographically confirmed) 7 (17) 1 (1) <.001
Medication use
 Zinc supplements 0 (0) 12 (10) .037d
 Iron supplements 5 (12) 7 (6) .202
 Magnesium supplements 16 (39) 26 (22)
 Vitamin D supplements 31 (76) 97 (84) .256
 Calcium supplements 15 (37) 37 (32) .584
 Proton pump inhibitors 21 (51) 37 (32) .028
 H2 receptor antagonists 3 (7) 5 (4) .431d
 Gastric acid suppressants 23 (56) 41 (35) .020
 Diuretics 15 (37) 37 (32) .584
 Antihypertensive 28 (68) 76 (66) .747
 Antibiotics 25 (61) 42 (36) .006
 Narcotic drugs 15 (37) 24 (21) .043

a Zinc deficiency was defined as serum zinc concentration less than 0.66 mcg/mL (normal range, 0.66 to 1.10).

b Data given as No. (%) unless otherwise noted.

c Significant weight loss was defined as weight loss >10% or >10 lb loss compared with 1 year prior.

d P values were estimated by Fisher exact test.

Abbreviation: SD, standard deviation.

×
Among medications, cases were more likely than controls to take gastric acid suppressants (23 [56%] vs 41 [35%]) and narcotics (15 [37%] vs 24 [21%]). Patients taking gastric acid suppressants had increased odds of lower zinc concentrations (odds ratio, 2.24; 95% CI, 1.08-4.63). There was no difference in the percentage of patients taking diuretics (15 [37%] vs 37 [32%]) between case and control groups. 
Laboratory Findings
The case group had a mean (SD) serum zinc concentration 0.58 (0.05) µg/ml, compared with the control group's mean (SD) of 0.80 (0.13) µg/ml (P<.001). Patients with zinc deficiency also had lower mean (SD) blood concentrations of calcium (9.09 [0.38] vs 9.27 [0.38]; P=.009); magnesium (1.92 [0.19] vs. 2.00 [0.21]; P=.046); albumin (3.45 [0.44] vs. 3.85 [0.37]; P<.001); and hemoglobin concentration (12.1 [1.6] vs 13.4 [2.48]; P <.001) compared with the control group (Table 2). 
Table 2.
Laboratory Findings of Adults With Zinc Deficiencya and Controls in an Adult Clinic
Zinc deficiency Control
Variables Laboratory results (SD) nb Laboratory results (SD) nc P value
Zinc (mcg/mL) 0.58 (0.05) 41 0.803 (0.13) 116 <.001d
Calcium 9.09 (0.38) 41 9.27 (0.38) 116 .009d
Magnesium 1.92 (0.19) 38 2.00 (0.21) 95 .046d
Hypomagnesemia 13% 5 of 38 11% 10 .665
Albumin (g/dL) 3.45 (0.44) 41 3.85 (0.37) 116 <.001d
Hypoalbuminemia (< 3.5 g/dL) 46% 19 11% 13 <.001d
Creatinine 1.03 (0.44) 41 0.97 (0.36) 116 .347
Total 25(OH) vitamin D level (ng/mL) 28.3 (9.9) 35 33.0 (12.8) 98 .053
D level < 20 ng/mL 14% 5 of 35 13% 13 .880
Hb level (g/dL) 12.1 (1.6) 41 13.4 (2.48) 116 .0003d
Hb <12.0 g/dL 51.2% 21 18.3% 21 of 115 <.001b

a Zinc deficiency was defined as serum zinc concentration less than 0.66 (mcg/mL).

b n out of 41 patients in the zinc deficiency case group, unless otherwise stated.

c n out of 116 patients in the control group, unless otherwise stated.

d Statistical significance.

Abbreviations: Hb, hemoglobin; SD, standard deviation.

Table 2.
Laboratory Findings of Adults With Zinc Deficiencya and Controls in an Adult Clinic
Zinc deficiency Control
Variables Laboratory results (SD) nb Laboratory results (SD) nc P value
Zinc (mcg/mL) 0.58 (0.05) 41 0.803 (0.13) 116 <.001d
Calcium 9.09 (0.38) 41 9.27 (0.38) 116 .009d
Magnesium 1.92 (0.19) 38 2.00 (0.21) 95 .046d
Hypomagnesemia 13% 5 of 38 11% 10 .665
Albumin (g/dL) 3.45 (0.44) 41 3.85 (0.37) 116 <.001d
Hypoalbuminemia (< 3.5 g/dL) 46% 19 11% 13 <.001d
Creatinine 1.03 (0.44) 41 0.97 (0.36) 116 .347
Total 25(OH) vitamin D level (ng/mL) 28.3 (9.9) 35 33.0 (12.8) 98 .053
D level < 20 ng/mL 14% 5 of 35 13% 13 .880
Hb level (g/dL) 12.1 (1.6) 41 13.4 (2.48) 116 .0003d
Hb <12.0 g/dL 51.2% 21 18.3% 21 of 115 <.001b

a Zinc deficiency was defined as serum zinc concentration less than 0.66 (mcg/mL).

b n out of 41 patients in the zinc deficiency case group, unless otherwise stated.

c n out of 116 patients in the control group, unless otherwise stated.

d Statistical significance.

Abbreviations: Hb, hemoglobin; SD, standard deviation.

×
Predictors of Zinc Deficiency and Zinc Status
The multiple logistic regression model for zinc deficiency identified that hip fracture (adjusted OR, 9.65; 95% CI, 1.69-55.15), nonhip fracture (adjusted OR, 11.52, 95% CI, 3.25-40.87), and low serum albumin concentration (adjusted OR, 5.17; 95% CI, 1.80-14.90) were independent factors associated with zinc deficiency, after adjusting for age, sex, BMI, and alcohol use (Table 3). Linear regression models for serum zinc concentration also identified that hip fractures (coefficient β=−0.127; 95% CI, −0.221 to −0.033), nonhip fractures (coefficient β=−0.100; 95% CI, −0.168 to −0.032), and low serum albumin (coefficient β=−.078; 95% CI, −0.138 to −0.019) were associated with zinc status after adjusting for the same variables (Table 4). When albumin and hemoglobin concentrations were analyzed as continuous variables in both models, albumin remained a significant independent factor associated with zinc deficiency and serum zinc status. 
Table 3.
Risk Factors Associated With Zinc Deficiencya (N=157)
Variablesb Adjusted OR 95% CI P value
Age (years) 1.04 0.98-1.11 .223
Sex (f=1; m=0) 0.94 0.340-2.59 .901
Body mass index 1.07 0.98-1.16 .136
Alcohol use (regular) 2.93 0.82-10.45 .097
Hip fractures in the past 9.65 1.69-55.15 .011
Nonhip fracture in the past 11.52 3.25-40.87 <.001
Albumin <3.5 g/dL (hypoalbuminemia) 5.17 1.80-14.90 .002
Anemia (Hb <12 g/dL) 1.73 0.60-4.95 .308

a Zinc deficiency was defined as serum zinc concentration less than 0.66 (mcg/mL).

b Variables were dichotomized as 1=yes, 0=no (baseline) except age and body mass index. Hosmer and Lemeshow goodness-of-fit test: χ2=2.514, df=8, P=.961.

Abbreviations: CI, confidence interval; f, female; m, male; OR, odds ratio.

Table 3.
Risk Factors Associated With Zinc Deficiencya (N=157)
Variablesb Adjusted OR 95% CI P value
Age (years) 1.04 0.98-1.11 .223
Sex (f=1; m=0) 0.94 0.340-2.59 .901
Body mass index 1.07 0.98-1.16 .136
Alcohol use (regular) 2.93 0.82-10.45 .097
Hip fractures in the past 9.65 1.69-55.15 .011
Nonhip fracture in the past 11.52 3.25-40.87 <.001
Albumin <3.5 g/dL (hypoalbuminemia) 5.17 1.80-14.90 .002
Anemia (Hb <12 g/dL) 1.73 0.60-4.95 .308

a Zinc deficiency was defined as serum zinc concentration less than 0.66 (mcg/mL).

b Variables were dichotomized as 1=yes, 0=no (baseline) except age and body mass index. Hosmer and Lemeshow goodness-of-fit test: χ2=2.514, df=8, P=.961.

Abbreviations: CI, confidence interval; f, female; m, male; OR, odds ratio.

×
Table 4.
Multiple Linear Regression Models of Serum Zinc Concentration (N=156)
Variablesa Coefficient, β 95% CI P value
Intercept 0.970 0.704 to 1.235 <.0001
Age −0.002 −0.004 to 0.001 .255
Sex (F=1; M=0) 0.009 −0.039 to 0.057 .726
Body mass index −0.002 −0.006 to 0.002 .387
Alcohol use (regular) −0.033 −0.098 to 0.032 .319
Hip fractures history −0.127 −0.221 to −0.033 .008
Nonhip fracture history −0.100 −0.168 to −0.032 .004
Albumin <3.5 g/dL (hypoalbuminemia) −0.078 −0.138 to −0.019 .010
Anemia (Hb <12 g/dL) −0.031 −0.088 to 0.026 .288

a Variables were dichotomized as 1=yes, 0=no except age and body mass index. R2 =0.228; adjusted R2=0.186.

Abbreviations: CI, confidence interval; F, female; Hb, hemoglobin; M, male.

Table 4.
Multiple Linear Regression Models of Serum Zinc Concentration (N=156)
Variablesa Coefficient, β 95% CI P value
Intercept 0.970 0.704 to 1.235 <.0001
Age −0.002 −0.004 to 0.001 .255
Sex (F=1; M=0) 0.009 −0.039 to 0.057 .726
Body mass index −0.002 −0.006 to 0.002 .387
Alcohol use (regular) −0.033 −0.098 to 0.032 .319
Hip fractures history −0.127 −0.221 to −0.033 .008
Nonhip fracture history −0.100 −0.168 to −0.032 .004
Albumin <3.5 g/dL (hypoalbuminemia) −0.078 −0.138 to −0.019 .010
Anemia (Hb <12 g/dL) −0.031 −0.088 to 0.026 .288

a Variables were dichotomized as 1=yes, 0=no except age and body mass index. R2 =0.228; adjusted R2=0.186.

Abbreviations: CI, confidence interval; F, female; Hb, hemoglobin; M, male.

×
Discussion
The current study found that 26% of adults in an outpatient clinic had zinc deficiency based on serum concentrations. These patients were also more likely to have lower concentrations of other nutritional biomarkers, such as albumin, calcium, magnesium, and hemoglobin. They had more medical events within 1 year before the index date of zinc measurement, such as hospitalization, receiving antibiotic therapy, and self-reported falls. Our study also demonstrated that a history of hip fractures, nonhip fractures, and lower albumin concentration were independently associated with lower serum zinc concentration and zinc deficiency. 
It has been estimated that zinc deficiency might affect 2 billion people globally, with as many as 25% of people at risk.4 This estimate was very close to our finding of 26% among outpatient clinic adults in southeast Ohio. A lower estimate of zinc deficiency was reported in a previous study14 in approximately 8% of 4347 US residents older than 10 years (NHANES 2011-2014 dataset). 
Our study demonstrated that previous hip and nonhip fractures were significantly associated with zinc deficiency after adjusting for age, sex, BMI, and alcohol use (Table 3). However, our findings could not establish a causal relationship between zinc status and fractures. The role of zinc in bone health has been reported by a few studies,20-25 with inconsistent reports26-28 partially due to small sample sizes among studies. A meta-analysis29 of 8 studies involving 2188 participants revealed that low serum zinc concentrations were a risk factor for osteoporosis along with other micronutrients (copper and iron). A population-based prospective cohort study30 of 6576 middle-aged Swedish men (46-68 years old) showed that those in the lowest decile of zinc intake (10 mg daily) had an almost 2-fold increased risk of fracture, as compared with those in the 4th and 5th quintiles of zinc intake, with adjustment for confounders, during a mean follow-up period of 2.4 years. Another study31 randomly assigned 147 premenarcheal girls aged 9 to 11 years to a daily oral zinc tablet (9 mg elemental zinc; n=75) or a placebo (n=72) for 4 weeks, and showed that supplementation significantly increased serum zinc concentrations and also increased serum bone formation markers (procollagen type 1 amino-terminal propeptide) concentrations. Another study32 demonstrated lower serum zinc concentrations in transfusion-dependent beta-thalassemic adolescent patients with lower bone mineral density; zinc supplementation of 25 mg/day for 18 months improved total-body bone mass in young patients (10-30 years, 32 participants) with thalassemia major in a small clinical trial.33 
Serum zinc concentrations may be affected by the status of zinc-binding proteins such as albumin, which binds 80% to 85% of serum zinc; the rest is bound to alpha 2-macroglobulin (5%-15%) and a small fraction to transferrin (<10%).5,15 Our study has shown that serum zinc concentration was negatively associated with hypoalbuminemia (Table 4). A similar coefficient was obtained between serum zinc concentrations and serum albumin when treating both measures as continuous variables. Thus, our study showed that lower albumin concentration or hypoalbuminemia was an independent predictor for lower serum zinc concentration status or zinc deficiency, in agreement with a prior study.14 
Zinc deficiency is often reported in people with inadequate dietary intake, heavy alcohol use,34 gastrointestinal disorders leading to malabsorption, liver disease and cirrhosis,35 diabetes mellitus,36 and use of certain medications leading to zinc depletion.4 The absorption of zinc can also be affected by high phytate-containing cereal protein intake.4 On the other hand, zinc supplementation decreases the absorption of copper37 and iron38 and may also affect magnesium balance.39 
Although some biomarkers such as metallothionein and zinc transporter of blood leukocytes have been studied for assessing zinc status,19,40-42 serum zinc concentration is considered reliable (and convenient) for assessing zinc status in adults and the elderly.9 Our study found that patients with lower serum zinc concentrations also have lower blood concentrations of calcium, magnesium, and albumin, which may serve as clinical indicators to prompt clinicians to test for serum zinc deficiency. Furthermore, patients who have suboptimal nutritional status with recent medical events (hospitalization, falls, fractures) and other conditions well known for the presentation of zinc deficiency—particularly dermatitis (such as acrodermatitis enteropathica), impaired wound healing, and frequent infections (due to low immunity)4—should be considered for zinc status evaluation. 
Our study had limitations. The sample size was relatively small, and data were from 1 study site. Some risk factors, such as age, gender, or ethnicity, may become significant when the sample size is large enough for data analysis. Our study's population was predominately white, and because of the small sample size, our study did not include race or ethnic group as a variable in the logistic regression analysis. Also, “normal” zinc concentrations may not necessarily indicate an adequate total body zinc reserve status since serum zinc concentration reflects only 0.1% of body zinc reserves. Convenient, reliable tools for assessing zinc status are needed for future studies. 
Additionally, a NHANES 2011-2014 study14 revealed that zinc concentrations are related to blood draw time, with afternoon/evening draws negatively associated with serum zinc concentrations. However, the timing of the blood draws was not considered in our data analysis, although most blood draws were performed before noon. Finally, our study did not include repeat measuring blood zinc concentration to exclude the possibility of laboratory errors. 
One strength of our study was that zinc concentrations and other nutritional biomarkers were obtained when patients had a stable health status. Documented fracture history before index dates were also confirmed by documented records, not by self-report. This study thus provides perspectives on nutritional deficiencies in some patients who have experienced fractures. Our findings provide rationale for new studies to determine whether repletion of zinc may facilitate their recovery, optimize their health status, or reduce future falls or fracture risks. 
Conclusion
This pilot prevalence study revealed that 26% of patients in an outpatient adult clinic had zinc deficiency based on serum zinc concentrations. Patients with a history of fractures and low albumin were at higher risk for zinc deficiency. Future randomized placebo-controlled trials may help determine the causal relationship between zinc status and fracture risk because understanding this association may be clinically valuable for fracture prevention. 
Acknowledgements
The authors thank Dr. Yang Li, PhD (Department of Biomedical Sciences, Heritage College of Osteopathic Medicine, Ohio University) for his critical review and comments on finalizing the manuscript. 
References
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Table 1.
Characteristics of Zinc Deficiency and Controls Among Adults at an Adult Clinic in Southeast Ohioa (N=157)
Variablesb Zinc deficiency case group (n=41) Control group (n=116) P value
Demographics
 Age, mean (SD) 82.6 (8.7) 78.2 (8.9) .007
 White 40 (98) 100 (86) .044
 Women 29 (71) 73 (63) .368
 Weight, lb (SD) 161.3 (42.1) 163.4 (38.6) .769
 Body mass index (SD) 28.6 (6.7) 27.9 (5.4) .479
 Alcohol use regularly 8 (20) 16 (14) .382
 Current smoker 5 (12) 11 (10) .622
 Past smoking history 17 (42) 51 (44) .781
Associated comorbidity
 Diabetes mellitus 10 (24) 22 (19) .459
 Hypothyroidism 9 (22) 27 (23) .862
 Gastroesophageal reflux disease 24 (59) 57 (49) .301
 Depression 23 (56) 56 (48) .389
Events in the past 1 year
 Hospitalization 18 (44) 18 (16) <.001
 Use of antibiotics 26 (63) 46 (40) .009
 Fall 23 (56) 14 (12) <.001
 Significant weight lossc 10 (25) 18 (16) .178
 Diarrhea (reported in past 3 months) 6 (15) 5 (4) .026
History of fractures
 All fracture 22 (54) 9 (8) <.001
 Hip fracture 7 (17) 3 (3) .0034d
 Nonhip fracture 15 (37) 7 (6) <.001
 Vertebral fracture (radiographically confirmed) 7 (17) 1 (1) <.001
Medication use
 Zinc supplements 0 (0) 12 (10) .037d
 Iron supplements 5 (12) 7 (6) .202
 Magnesium supplements 16 (39) 26 (22)
 Vitamin D supplements 31 (76) 97 (84) .256
 Calcium supplements 15 (37) 37 (32) .584
 Proton pump inhibitors 21 (51) 37 (32) .028
 H2 receptor antagonists 3 (7) 5 (4) .431d
 Gastric acid suppressants 23 (56) 41 (35) .020
 Diuretics 15 (37) 37 (32) .584
 Antihypertensive 28 (68) 76 (66) .747
 Antibiotics 25 (61) 42 (36) .006
 Narcotic drugs 15 (37) 24 (21) .043

a Zinc deficiency was defined as serum zinc concentration less than 0.66 mcg/mL (normal range, 0.66 to 1.10).

b Data given as No. (%) unless otherwise noted.

c Significant weight loss was defined as weight loss >10% or >10 lb loss compared with 1 year prior.

d P values were estimated by Fisher exact test.

Abbreviation: SD, standard deviation.

Table 1.
Characteristics of Zinc Deficiency and Controls Among Adults at an Adult Clinic in Southeast Ohioa (N=157)
Variablesb Zinc deficiency case group (n=41) Control group (n=116) P value
Demographics
 Age, mean (SD) 82.6 (8.7) 78.2 (8.9) .007
 White 40 (98) 100 (86) .044
 Women 29 (71) 73 (63) .368
 Weight, lb (SD) 161.3 (42.1) 163.4 (38.6) .769
 Body mass index (SD) 28.6 (6.7) 27.9 (5.4) .479
 Alcohol use regularly 8 (20) 16 (14) .382
 Current smoker 5 (12) 11 (10) .622
 Past smoking history 17 (42) 51 (44) .781
Associated comorbidity
 Diabetes mellitus 10 (24) 22 (19) .459
 Hypothyroidism 9 (22) 27 (23) .862
 Gastroesophageal reflux disease 24 (59) 57 (49) .301
 Depression 23 (56) 56 (48) .389
Events in the past 1 year
 Hospitalization 18 (44) 18 (16) <.001
 Use of antibiotics 26 (63) 46 (40) .009
 Fall 23 (56) 14 (12) <.001
 Significant weight lossc 10 (25) 18 (16) .178
 Diarrhea (reported in past 3 months) 6 (15) 5 (4) .026
History of fractures
 All fracture 22 (54) 9 (8) <.001
 Hip fracture 7 (17) 3 (3) .0034d
 Nonhip fracture 15 (37) 7 (6) <.001
 Vertebral fracture (radiographically confirmed) 7 (17) 1 (1) <.001
Medication use
 Zinc supplements 0 (0) 12 (10) .037d
 Iron supplements 5 (12) 7 (6) .202
 Magnesium supplements 16 (39) 26 (22)
 Vitamin D supplements 31 (76) 97 (84) .256
 Calcium supplements 15 (37) 37 (32) .584
 Proton pump inhibitors 21 (51) 37 (32) .028
 H2 receptor antagonists 3 (7) 5 (4) .431d
 Gastric acid suppressants 23 (56) 41 (35) .020
 Diuretics 15 (37) 37 (32) .584
 Antihypertensive 28 (68) 76 (66) .747
 Antibiotics 25 (61) 42 (36) .006
 Narcotic drugs 15 (37) 24 (21) .043

a Zinc deficiency was defined as serum zinc concentration less than 0.66 mcg/mL (normal range, 0.66 to 1.10).

b Data given as No. (%) unless otherwise noted.

c Significant weight loss was defined as weight loss >10% or >10 lb loss compared with 1 year prior.

d P values were estimated by Fisher exact test.

Abbreviation: SD, standard deviation.

×
Table 2.
Laboratory Findings of Adults With Zinc Deficiencya and Controls in an Adult Clinic
Zinc deficiency Control
Variables Laboratory results (SD) nb Laboratory results (SD) nc P value
Zinc (mcg/mL) 0.58 (0.05) 41 0.803 (0.13) 116 <.001d
Calcium 9.09 (0.38) 41 9.27 (0.38) 116 .009d
Magnesium 1.92 (0.19) 38 2.00 (0.21) 95 .046d
Hypomagnesemia 13% 5 of 38 11% 10 .665
Albumin (g/dL) 3.45 (0.44) 41 3.85 (0.37) 116 <.001d
Hypoalbuminemia (< 3.5 g/dL) 46% 19 11% 13 <.001d
Creatinine 1.03 (0.44) 41 0.97 (0.36) 116 .347
Total 25(OH) vitamin D level (ng/mL) 28.3 (9.9) 35 33.0 (12.8) 98 .053
D level < 20 ng/mL 14% 5 of 35 13% 13 .880
Hb level (g/dL) 12.1 (1.6) 41 13.4 (2.48) 116 .0003d
Hb <12.0 g/dL 51.2% 21 18.3% 21 of 115 <.001b

a Zinc deficiency was defined as serum zinc concentration less than 0.66 (mcg/mL).

b n out of 41 patients in the zinc deficiency case group, unless otherwise stated.

c n out of 116 patients in the control group, unless otherwise stated.

d Statistical significance.

Abbreviations: Hb, hemoglobin; SD, standard deviation.

Table 2.
Laboratory Findings of Adults With Zinc Deficiencya and Controls in an Adult Clinic
Zinc deficiency Control
Variables Laboratory results (SD) nb Laboratory results (SD) nc P value
Zinc (mcg/mL) 0.58 (0.05) 41 0.803 (0.13) 116 <.001d
Calcium 9.09 (0.38) 41 9.27 (0.38) 116 .009d
Magnesium 1.92 (0.19) 38 2.00 (0.21) 95 .046d
Hypomagnesemia 13% 5 of 38 11% 10 .665
Albumin (g/dL) 3.45 (0.44) 41 3.85 (0.37) 116 <.001d
Hypoalbuminemia (< 3.5 g/dL) 46% 19 11% 13 <.001d
Creatinine 1.03 (0.44) 41 0.97 (0.36) 116 .347
Total 25(OH) vitamin D level (ng/mL) 28.3 (9.9) 35 33.0 (12.8) 98 .053
D level < 20 ng/mL 14% 5 of 35 13% 13 .880
Hb level (g/dL) 12.1 (1.6) 41 13.4 (2.48) 116 .0003d
Hb <12.0 g/dL 51.2% 21 18.3% 21 of 115 <.001b

a Zinc deficiency was defined as serum zinc concentration less than 0.66 (mcg/mL).

b n out of 41 patients in the zinc deficiency case group, unless otherwise stated.

c n out of 116 patients in the control group, unless otherwise stated.

d Statistical significance.

Abbreviations: Hb, hemoglobin; SD, standard deviation.

×
Table 3.
Risk Factors Associated With Zinc Deficiencya (N=157)
Variablesb Adjusted OR 95% CI P value
Age (years) 1.04 0.98-1.11 .223
Sex (f=1; m=0) 0.94 0.340-2.59 .901
Body mass index 1.07 0.98-1.16 .136
Alcohol use (regular) 2.93 0.82-10.45 .097
Hip fractures in the past 9.65 1.69-55.15 .011
Nonhip fracture in the past 11.52 3.25-40.87 <.001
Albumin <3.5 g/dL (hypoalbuminemia) 5.17 1.80-14.90 .002
Anemia (Hb <12 g/dL) 1.73 0.60-4.95 .308

a Zinc deficiency was defined as serum zinc concentration less than 0.66 (mcg/mL).

b Variables were dichotomized as 1=yes, 0=no (baseline) except age and body mass index. Hosmer and Lemeshow goodness-of-fit test: χ2=2.514, df=8, P=.961.

Abbreviations: CI, confidence interval; f, female; m, male; OR, odds ratio.

Table 3.
Risk Factors Associated With Zinc Deficiencya (N=157)
Variablesb Adjusted OR 95% CI P value
Age (years) 1.04 0.98-1.11 .223
Sex (f=1; m=0) 0.94 0.340-2.59 .901
Body mass index 1.07 0.98-1.16 .136
Alcohol use (regular) 2.93 0.82-10.45 .097
Hip fractures in the past 9.65 1.69-55.15 .011
Nonhip fracture in the past 11.52 3.25-40.87 <.001
Albumin <3.5 g/dL (hypoalbuminemia) 5.17 1.80-14.90 .002
Anemia (Hb <12 g/dL) 1.73 0.60-4.95 .308

a Zinc deficiency was defined as serum zinc concentration less than 0.66 (mcg/mL).

b Variables were dichotomized as 1=yes, 0=no (baseline) except age and body mass index. Hosmer and Lemeshow goodness-of-fit test: χ2=2.514, df=8, P=.961.

Abbreviations: CI, confidence interval; f, female; m, male; OR, odds ratio.

×
Table 4.
Multiple Linear Regression Models of Serum Zinc Concentration (N=156)
Variablesa Coefficient, β 95% CI P value
Intercept 0.970 0.704 to 1.235 <.0001
Age −0.002 −0.004 to 0.001 .255
Sex (F=1; M=0) 0.009 −0.039 to 0.057 .726
Body mass index −0.002 −0.006 to 0.002 .387
Alcohol use (regular) −0.033 −0.098 to 0.032 .319
Hip fractures history −0.127 −0.221 to −0.033 .008
Nonhip fracture history −0.100 −0.168 to −0.032 .004
Albumin <3.5 g/dL (hypoalbuminemia) −0.078 −0.138 to −0.019 .010
Anemia (Hb <12 g/dL) −0.031 −0.088 to 0.026 .288

a Variables were dichotomized as 1=yes, 0=no except age and body mass index. R2 =0.228; adjusted R2=0.186.

Abbreviations: CI, confidence interval; F, female; Hb, hemoglobin; M, male.

Table 4.
Multiple Linear Regression Models of Serum Zinc Concentration (N=156)
Variablesa Coefficient, β 95% CI P value
Intercept 0.970 0.704 to 1.235 <.0001
Age −0.002 −0.004 to 0.001 .255
Sex (F=1; M=0) 0.009 −0.039 to 0.057 .726
Body mass index −0.002 −0.006 to 0.002 .387
Alcohol use (regular) −0.033 −0.098 to 0.032 .319
Hip fractures history −0.127 −0.221 to −0.033 .008
Nonhip fracture history −0.100 −0.168 to −0.032 .004
Albumin <3.5 g/dL (hypoalbuminemia) −0.078 −0.138 to −0.019 .010
Anemia (Hb <12 g/dL) −0.031 −0.088 to 0.026 .288

a Variables were dichotomized as 1=yes, 0=no except age and body mass index. R2 =0.228; adjusted R2=0.186.

Abbreviations: CI, confidence interval; F, female; Hb, hemoglobin; M, male.

×