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Serum Zinc Concentrations Correlate with Mental and Physical Status of Nursing Home Residents



Zinc (Zn) is one of the most important trace elements in the body. Zn deficiency seems to play a role in the development of age-related diseases and impairment of quality of life. Zn status has been especially studied in free-living or hospitalised people, but data from older residents of nursing homes are scarce. This study aimed to determine the Zn status among the older individuals in correlation to their mental and physical performance.


A total of 100 participants aged between 60-102 years were recruited between October 2010 and May 2012 at the nursing home in Bialystok (Poland). Zn status was evaluated by determining the concentration in serum by flame atomic absorption spectrometry. Anthropometric variables and fitness score (FS) were measured. Abbreviated Mental Test Score (AMTS), Geriatric Depression Scale (GDS), Self-Rated Health (SRH), independence in Activities of Daily Living (ADL) were recorded.

Results and Discussion

The mean serum Zn concentration was 0.83±0.20 mg/L, 28% of residents had Zn deficiency. Cognitive functions were impaired (AMTS≤8) in 45% of the studied persons and 48% showed depressive symptoms (GDS≥1). The ability to independently perform activities of daily living (ADL = 6) was found in 61% of participants, but most of them (90%) had weak body type (FS<70), correlating with GDS, SRH and body mass index (BMI). Serum Zn concentration correlated with mental efficiency and was statistically significantly higher in older people with normal cognitive function and without depression than in patients with memory impairment and showing depressive symptoms.


Nursing home residents seem at risk of marginal Zn status, which correlates with their mental status as measured by the AMTS and GDS. Their low FS is associated with mental health deterioration and obesity.


The growing percentage of older people in the world indicates an increasing number of individuals with serious health problems, functional disability and multiple diseases. In addition to many somatic symptoms and chronic diseases of old age, mental disorders are a common problem—these include cognitive impairment, syndromes of dementia and depression, often unrecognized. Since depression is a common health problem in old age, with prevalence rates of up to 46% in institutionalized older people, there is a need for early diagnosis and treatment, which may contribute to improving their quality of life [13].

An increased interest is observed in biomarkers of aging and distinct age-related changes such as disabilities, physical function decline, frailty, diseases of old age, and mortality [4, 5]. A decline in physical performance and function often marks the early stage of the ageing process [6]. Therefore, there is a need to identify those biomarkers related to the age-associated decline in mental and physical performance. It has been shown that low serum micronutrient concentrations are an independent risk factor for frailty among disabled older women, and the risk of frailty increases with the number of micronutrient deficiencies [7].

Nutritional deficiencies resulting in an increased incidence of age-related pathologies are well documented in ageing individuals [8]. Numerous clinical and epidemiological data focused on the importance of nutritional micronutrients status in maintaining performance capacities and quality of life in ageing population [9]. Since Zn affects many age-related functions [10], it is essential to maintain or restore an optimal Zn status in older people. The available studies on Zn status describe free-living or hospitalised people and focus on inadequate Zn intake as well as on relation to humoral immune function in ageing [11, 12].

Zinc in the synaptic vesicles of neurons plays a role in brain activities like learning and memory function. Zn acts as a neurotransmitter [13, 14]. It has been shown that Zn deficiency is associated with certain problems commonly seen in the older population, such as frequent infection episodes, loss of taste and appetite, difficulty seeing at night, defect in bone mineralization, hair loss, depression, difficulty in concentration and mental lethargy [10, 15].

There is a limited number of published reports on the relationship between Zn status and mental and physical health among nursing home residents. Therefore, the aim of the present study was to examine the Zn status in a nursing home population and to determine whether Zn serum concentration is related to their mental and physical performance.



The study was performed between October 2010 and May 2012. All of the 130 residents living in the nursing home (Bialystok, Poland) were invited to participate in the study. A total of 30 residents or their legal representatives, either declined to participate or it was not possible to contact them. All study participants were informed about the objectives of the study and the written consent was obtained from each participant or their legally authorized representative. The study protocol was approved by the Local Bioethical Committee of Medical University of Bialystok (UMB-R-I-002/259/2008). All participants completed a study questionnaire with assistance of the researchers during face-to-face interviews. The blood drawing was done on the same day as the tests. Fasting blood samples were collected in the Vacutainer Systems tubes containing clot activator (Becton Dickinson, France). The blood was centrifuged. The serum was removed and kept frozen at -80°C.

Data on age, number of diagnosed diseases and dosages of prescribed medications were collected from the residents’ files by a physician. The participants took only the medications prescribed by their medical doctor and they did not take any supplements. Anthropometric variables included height and weight measured to the nearest 0.1 cm and 0.1 kg, respectively, using height-measuring equipment connected with an electronic scale (AXIS B150L, Seca, Gdańsk, Poland) while the subjects were wearing light-weight clothes. Then, body mass index (BMI) was computed as the ratio of weight (kg) to height squared (m2). BMI was used to assess the prevalence of overweight (25–29.9 kg/m2) and obesity (≥30 kg/m2) according to WHO criteria [16].

We used the bioelectrical impedance analysis system (InBody720, Biospace, Seoul, Korea) to evaluate the mass of muscle and fat tissue in the body composition of participants and based on the results we determined their fitness score (FS). A value of less than 70 points indicated a weak body type, a range of 70 to 90 points—normal body type and greater than 90 points—athletic body type.

Serum zinc determination

Zn status was evaluated by determining the serum Zn concentration using flame atomic absorption spectrometry on Z-2000 instrument (Hitachi, Japan) with Zeeman background correction [17]. All samples were run in duplicate. Serum concentration <0.7 mg/L was regarded as Zn deficiency [18].

The method of Zn determination was verified using certified reference material (Seronorm Trace Elements Serum L-1, 0903106, Sero AS, Norway). The accuracy (expressed as a percentage of the error) was 1.96% and coefficient of variance (indicator of the precision of this method) was 2.56%. These values did not exceed 2% and 5%, respectively. Moreover, our Department has participated in a quality control program for trace elements’ analysis supervised by the Institute of Nuclear Chemistry and Technology and the National Institute of Public Health (Warsaw, Poland) and our results of the quality control analyses were consistently categorized as being in agreement with reference values.

Mental state

Cognitive impairment among the study participants was evaluated using the Abbreviated Mental Test Score (AMTS), a brief 10-item survey. Each question answered correctly scored one point and a score of 8 or less suggested cognitive impairment at the time of testing. AMTS was introduced by Hodkinson in 1972 [19]. It is a rapid tool for assessing cognitive function and it is especially useful in determining the risk of dementia in older patients. With time, AMTS has become more widely used in health care, e.g. to assess confusion or cognitive impairment and has been mainly validated in older subjects. Even though it is similar to the Mini Mental State Examination (MMSE), the AMTS does not require reading, writing or drawing and it does not strictly depend on the educational level; overall, a strong linear relationship has been demonstrated between the MMSE and AMTS [20]. A meta-analysis of studies comparing the AMTS (cut-off value of <8) with dementia as defined by the reference standard, showed that the AMTS allows 94% sensitivity and 74% specificity for the diagnosis of dementia [21]. According to the meta-analysis, AMTS is a proper screening instrument.

Emotional status of the study population was examined using the Geriatric Depression Scale (GDS) validated in nursing home residents [22]. We decided to use the short version GDS with only 4 ‘Yes/No’ questions. A score of 1 point or above indicates depression. The short version GDS is not only convenient and saving resources, but it is also more acceptable to older people and can be used in lieu of the longer versions [23, 24].

Self-Rated Health (SRH) was assessed using a 5-point Likert scale (from 1 to 5) with questions pertaining to the respondent’s perceived overall health: “In general, would you say your health is: very poor, poor, almost good, good or excellent?” [25, 26].

Physical function

Changes in the functional status of older persons are common, multicausal, and can result from a variety of diseases. The Katz index of independence in Activities of Daily Living (ADL) is the most appropriate instrument to assess functional status. The index ranks the adequacy of performing six functions i.e. bathing, dressing, toileting, transferring, continence and feeding. Patients are scored ‘Yes/No’ for independence in each of the functions. A score of 6 indicates full function, 4 indicates moderate impairment, and 2 or less indicates severe functional impairment [2729].

Statistical analyses

Statistical analyses were performed using Statistica software version 10.0 PL for Windows (StatSoft, Cracow, Poland). Metric data were tested for normal distribution by the Kolmogorov-Smirnov and the Shapiro-Wilk tests and visual inspection of the Quantile-Quantile (Q-Q) plots. Results are given as mean and standard deviation (SD) and as median and interquartile range (IQR). Normally and non-normally distributed variables of two independent groups were compared using the Student’s t-test and the Mann-Whitney U test, respectively. Correlations between the parameters were described by the Spearman’s rank correlation coefficients. To compare the qualitative variables we used the chi-square test for independence. Analysis of variance was performed using ANOVA tests and post-hoc NIR Fisher’s test. We assessed the effects of the analysed parameters on the variability of Zn concentration using backward multiple regression. A p-value of less than 0.05 was considered statistically significant.


Patients characteristics and their test results are presented in Table 1. The correlations between the characteristics and test results are given in Table 2. The mean age of the study participants was 76±11 years (range: 60–102), women (79.5±9.8 years) were older (p<0.001) than men (72.2±10.5 years). Overweight or obesity were found in 64% of the examined nursing home residents. In addition, BMI correlated with FS (r = -0.48, p<0.001), with SRH (r = -0.24, p = 0.014) and with GDS (r = 0.20, p = 0.047). Out of all study participants, 64% had 3 or more diseases diagnosed and 95% had been taking at least one medication. The number of diseases showed weak but positive correlations with age (r = 0.21, p = 0.038) and with BMI (r = 0.22, p = 0.028), and negative correlations with FS (r = -0.30, p = 0.002) and SRH (r = -0.39, p<0.001). Similarly, the number of prescribed medications positively correlated with age (r = 0.20, p = 0.044) and BMI (r = 0.22, p = 0.025), and negatively with FS (r = -0.21, p = 0.046) and AMTS (r = -0.20, p = 0.041).

Table 2. Spearman’s rank correlation coefficients between measured parameters (and p values for significant correlation).

Serum Zn concentrations in our subjects ranged from 0.43 mg/L to 1.39 mg/L. Categorization of Zn concentration showed proper Zn status in most individuals—the prevalence of Zn deficiency was 28%. The change in the Zn status was associated with age (r = -0.28, p = 0.005) and with mental health parameters: AMTS (r = 0.38, p<0.001) and GDS (r = -0.28, p = 0.006). Chi-square test for independence (Table 3) also indicated an association of Zn status with age (χ2 = 11.32, df = 4, p = 0.023). We determined that Zn concentration was below normal in only 17% of the participants aged ≤70 years, and in 43% of those aged >80 years. The ANOVA test showed that gender did not influence the Zn status and no interaction between age and gender was found. Age affected the serum Zn concentration in both men and women, particularly in the oldest age. This trend was clearly marked for men (Fig. 1). Post-hoc NIR Fisher’s test underlined lower serum Zn concentration in the oldest participants (>80 years) compared to those below 70 years of age (p = 0.021) and those aged 70–80 years (p = 0.037).

Table 3. Measured parameters according to zinc status evaluated by serum zinc (Zn mg/L) concentration.

Fig 1. Influence of age and gender on zinc status.

The results are obtained in ANOVA test. F(2, 94) = 0.5479, p = 0.580. Vertical bars represent the 0.95 confidence intervals. F-female, M-male.

The normal cognitive functions (AMTS>8) were found in 55% of the studied individuals (Table 1). The prevalence rate of well-being (SRH≥3) was 89% in the group with the normal cognitive functions and 69% in patients with impaired cognitive functions, which showed a significant difference (χ2 = 6.31, df = 1, p = 0.012). The difference in the prevalence rate of ADL = 6 was also significant (χ2 = 12.13, df = 1, p<0.001) in these groups—76% and 42%, respectively. Additionally, we found a moderate negative relationship between AMTS and age (Table 2).

Over a half of the examined participants (52%) showed no signs of depression (Table 1). Among the 48 residents considered to have depressive symptoms according to the GDS, only 3 had a documented diagnosis of depression and 14 had mood disorders in their medical charts. Moreover, the FS was higher (p<0.001) in patients with GDS = 0 vs. patients with signs of depression and additionally a positive correlation was found between SRH and FS (r = 0.36, p<0.001).

The majority of patients had a weak body type (FS below 70 points). The ability to independently perform activities of daily living (ADL = 6) was found in 61% of participants. We observed a moderate positive correlation of ADL with SRH (r = 0.30, p = 0.002) and a weak positive correlation with AMTS (r = 0.26, p = 0.009).

Serum Zn concentrations were higher (p = 0.001) in subjects with unimpaired cognitive function (0.89 ± 0.20 mg/L) compared to subjects with memory impairment (0.76±0.19 mg/L) (Fig. 2). Participants showing signs of depression had lower (p = 0.005) serum Zn concentration (0.77±0.17 mg/L) than those without depression (0.89±0.22 mg/L), but there was no association (p = 0.081) between serum Zn concentration and the intensity of depression as shown by the ANOVA test (Fig. 3).

Fig 2. Zinc levels in groups with normal cognitive function and with memory impairment.

Asterisk denotes statistically significant difference in serum zinc concentration in the two groups obtained from the Student’s t-test (* p = 0.001). M—mean, SE—standard error

Fig 3. Association between serum zinc concentration and intensity of depression.

The results are obtained in ANOVA analysis of variance: F(4,95) = 2.1482, p = 0.081. Vertical bars represent the 0.95 confidence intervals.

Backward multiple regression analysis was performed, in which the insignificant independent variables were removed one by one i.e. number of medications, BMI, FS, number of diseases, ADL, SRH, age. The obtained results showed that the values of AMTS and GDS together explain 14% of the variation in serum Zn concentration (Table 4).

Table 4. The variability in serum zinc concentration depending on the tested parameters.


Data on Zn status among older residents of nursing homes are scarce. To the best of our knowledge, this is the first study that attempts to find a relationship between the Zn status and the mental and physical health in that population.

Plasma or serum Zn concentration is the most commonly and frequently used index for evaluating the probability of Zn deficiency [30]. In the present study, the mean serum Zn concentrations in men and women were 0.84±0.22 mg/L and 0.82±0.19 mg/L, respectively. Our results are in line with other studies i.e. the NHANES II study (1976–1980) [31], which reported 0.87 mg/L and 0.82mg/L, and the AREDS study, reporting 0.85 mg/L and 0.82 mg/L [32]. Furthermore, our obtained values are very close to those reported in Rancho Bernardo study [33] where the mean serum Zn concentration in men was 0.83 mg/L and are also similar to values observed in women from the SU.VI.MAX study, 0.84 mg/L [34]. Our results are slightly higher than the values determined among postmenopausal women in France, 0.80 mg/L [35] or in the United States, 0.75 mgl/L [36].

The percentage of subjects with serum Zn concentration below 0.7mg/L, which is usually considered as the cut-off level for Zn deficiency [18], was 28%. Our findings are comparable with studies carried out in hospitalised elderly people, in which 28% [11] or 38% [12] had plasma Zn concentration below the reference range. This high prevalence of Zn deficiency in nursing home residents is very different from data observed in free-living older population, in whom the reported prevalence rate is 5–6% among healthy subjects participating in the European study ZENITH, 5% in a study in Boston and 3–4% in the Euronut-Seneca European-based study [34, 37].

We observed an age-related change in Zn status (r = -0.28; p = 0.005), which is not in line with the findings of Del Corso et al. [38] but confirms the data by Ravaglia et al. [39]. We found that the prevalence rate of Zn deficiency was 2.5-fold higher among the oldest participants (>80 years) than among persons younger than 70 years.

In our study population we did not find gender differences in Zn status, which is consistent with results of several other studies [4042].

Grønli et al. [43] shows that Zn deficiency is very common among psychogeriatric patients and it is more prominent in patients suffering from psychiatric disorders other than depression. To our knowledge, no previous studies examined Zn status in nursing home residents with relation to memory function. In our present research, we observed reduced serum Zn concentration in people with memory impairment what indicates that Zn status correlates with cognitive functions.

The relatively high number of individuals with symptoms of depression (48%) revealed in the GDS test is in concordance with the literature [1, 3], however, it should be noted that only 6% of the examined individuals had a documented diagnosis of depression. These findings indicate that GDS test should be routinely performed among nursing home residents since untreated depression negatively affects the quality of life and well-being [44] and can increase mortality [45]. Additionally, in our study we found that older people without symptoms of depression had more athletic body type in comparison to the subjects with depression (p<0.001). Despite growing evidence that depression is a problem, especially in the institutionalised elderly persons, little attention is paid to this issue [3]. In the present study, we found a correlation between the serum Zn concentration and the emotional status—measured by GDS, and almost 2-fold higher prevalence of Zn deficiency in persons with symptoms of depression. This observation is in contrast to the studies by Siwek et al. [46] and Maes et al. [47], but is in line with other studies [48, 49], in which the authors detected a significant correlation. Additionally, a more detailed statistical analysis of our data showed that the magnitude of serum Zn decline did not reflect the severity of the depression. Generally, we found that the residents with depressive symptoms had lower serum Zn concentration (p = 0.005). Similar dependence was observed in clinical studies among patients diagnosed with depression when compared to healthy individuals [47, 4951].

As the highest Zn concentration in mice was found in the hippocampus region [52], this region seems to be most vulnerable to Zn deficiency [53, 54]. It is this region of the brain which plays a critical role in memory, learning and neurogenesis [54]. In the present study we detected lowered serum Zn concentrations in subjects with cognitive impairment and signs of depression, and found that the values of AMTS and GDS together explain 14% of the variation in concentration of serum Zn. Moreover, a study performed among the community-dwelling elderly persons shows a possible beneficial effect of Zn use in reducing cognitive decline [55]. However, the observed lowered Zn status in older people with cognitive dysfunction requires further investigation.


Nursing home residents seem to have low Zn status that correlates with their mental health. Their low FS is associated with mental health deterioration and obesity. Our findings highlight the desirability of monitoring the concentration of Zn in serum of older people.


The authors would like to thank the residents who participated in this study and assoc. prof. K. Socha for supporting this research and E. Karpińska for collecting some of the data. The study was conducted with the use of equipment purchased by Medical University of Bialystok as part of the OP DEP 2007–2013, Priority Axis I.3, contract No. POPW.01.03.00–20–022/09.

Author Contributions

Conceived and designed the experiments: RMŻ. Performed the experiments: RMŻ AG. Analyzed the data: RMŻ MHB. Contributed reagents/materials/analysis tools: RMŻ. Wrote the paper: RMŻ MHB.


  1. 1. Jongenelis K, Pot AM, Eisses AM, Beekman AT, Kluiter H, et al. (2004) Prevalence and risk indicators of depression in elderly nursing home patients: the AGED study. J Affect Disord 83: 135–142. pmid:15555706
  2. 2. Webber AP, Martin JL, Harker JO, Josephson KR, Rubenstein LZ, et al. (2005) Depression in older patients admitted for postacute nursing home rehabilitation. J Am Geriatr Soc 53: 1017–1022. pmid:15935027
  3. 3. Teresi J, Abrams R, Holmes D, Ramirez M, Eimicke J (2001) Prevalence of depression and depression recognition in nursing homes. Soc Psychiatry Psychiatr Epidemiol 36: 613–620. pmid:11838834
  4. 4. Gluckman PD, Hanson MA (2004) Living with the past: evolution, development, and patterns of disease. Science 305: 1733–1736. pmid:15375258
  5. 5. Rockwood K, Stolee P, McDowell I (1996) Factors associated with institutionalization of older people in Canada: testing a multifactorial definition of frailty. J Am Geriatr Soc 44: 578–582. pmid:8617909
  6. 6. Guralnik JM, Ferrucci L, Simonsick EM, Salive ME, Wallace RB (1995) Lower-extremity function in persons over the age of 70 years as a predictor of subsequent disability. N Engl J Med 332: 556–561. pmid:7838189
  7. 7. Semba RD, Bartali B, Zhou J, Blaum C, Ko CW, et al. (2006) Low serum micronutrient concentrations predict frailty among older women living in the community. J Gerontol A Biol Sci Med Sci 61: 594–599. pmid:16799142
  8. 8. Meydani M (2001) Nutrition interventions in aging and age associated disease. Ann N Y Acad Sci 928: 226–235. pmid:11795514
  9. 9. Bartali B, Semba RD, Frongillo EA, Varadhan R, Ricks MO, et al. (2006) Low micronutrient levels as a predictor of incident disability in older women. Arch Intern Med 166: 2335–2340. pmid:17130386
  10. 10. Meunier N, O’Connor JM, Maiani G, Cashman KD, Secker DL, et al. (2005) Importance of zinc in the elderly: the ZENITH study. Eur J Clin Nutr 59: S1–4. pmid:16255071
  11. 11. Pepersack T, Rotsaert P, Benoit F, Willems D, Fuss M, et al. (2001) Prevalence of zinc deficiency and its clinical relevance among hospitalised elderly. Arch Gerontol Geriatr 33: 243–253. pmid:15374021
  12. 12. Schmuck A, Roussel AM, Arnaud J, Ducros V, Favier A, et al. (1996) Analyzed dietary intakes, plasma concentrations of zinc, copper, and selenium, and related antioxidant enzyme activities in hospitalized elderly women. J Am Coll Nutr 15: 462–468. pmid:8892172
  13. 13. Smart TG, Hosie AM, Miller PS (2004) Zn2+ ions: modulators of excitatory and inhibitory synaptic activity. Neuroscientist 10: 432–442. pmid:15359010
  14. 14. Paoletti P, Vergnano AM, Barbour B, Casado M (2009) Zinc at glutamatergic synapses. Neuroscience 158: 126–136. pmid:18353558
  15. 15. Hambidge M (2000) Human zinc deficiency. J Nutr 130: 1344S–1349S. pmid:10801941
  16. 16. World Health Organization (2013) Obesity and overweight. WHO Fact Sheet N°311, March 2013.
  17. 17. Socha K, Borawska MH, Mariak Z, Kochanowicz J, Markiewicz R (2009) Diet and content of zinc in serum of patients with brain aneurysm. Fresen Environ Bull 18: 1932–1936.
  18. 18. Neumeister B, Besenthal J, Bohm BO (2013) Klinikleitfaden Labordiagnostik. 4th ed. Munchen: Elsevier Urban&Fischer Verlag.
  19. 19. Hodkinson HM (1972) Evaluation of a mental test score for assessment of mental impairment in the elderly. Age Ageing 1: 233–238. pmid:4669880
  20. 20. Swain DG AG, Nightingale PG (1999) Cognitive assessment in elderly patients admitted to hospital: the relationship between the Abbreviated Mental Test and the Mini-Mental State Examination. Clin Rehabil 13: 503–508. pmid:10588537
  21. 21. Jackson TA, Naqvi SH, Sheehan B (2013) Screening for dementia in general hospital inpatients: a systematic review and meta-analysis of available instruments. Age Ageing 42: 689–695. pmid:24100618
  22. 22. McGivney SA, Mulvihill M, Taylor B (1994) Validating the GDS depression screen in the nursing home. J Am Geriatr Soc 42: 490–492. pmid:8176142
  23. 23. D’Ath P, Katona P, Mullan E, Evans S, Katona C (1994) Screening, detection and management of depression in elderly primary care attenders. I: The acceptability and performance of the 15 item Geriatric Depression Scale (GDS15) and the development of short versions. Fam Pract 11: 260–266. pmid:7843514
  24. 24. Cheng ST, Chan AC (2005) Comparative performance of long and short forms of the Geriatric Depression Scale in mildly demented Chinese. Int J Geriatr Psychiatry 20: 1131–1137. pmid:16315157
  25. 25. Blazer DG, Houpt JL (1979) Perception of poor health in the healthy older adult. J Am Geriatr Soc 27: 330–334. pmid:448000
  26. 26. Perruccio AV, Badley EM, Hogg-Johnson S, Davis AM (2010) Characterizing self-rated health during a period of changing health status. Soc Sci Med 71: 1636–1643. pmid:20832154
  27. 27. Katz S, Ford AB, Moskowitz RW, Jackson BA, Jaffe MW (1963) Studies of illness in the aged. The index of ADL: a standardized measure of biological and psychosocial function. JAMA 185: 914–919. pmid:14044222
  28. 28. Hoshi T, Yuasa M, Yang S, Kurimori S, Sakurai N, et al. (2013) Causal relationships between survival rates, dietary and lifestyle habits, socioeconomic status and physical, mental and social health in elderly urban dwellers in Japan: A chronological study. Health 5: 1303–1312.
  29. 29. Laudisio A, Marzetti E, Pagano F, Cocchi A, Franceschi C, et al. (2008) Association of metabolic syndrome with cognitive function: the role of sex and age. Clin Nutr 27: 747–754. pmid:18715681
  30. 30. Prasad AS, Oberleas D, Halsted JA (1965) Determination of zinc in biological fluids by atomic absorption spectrophotometry in normal and cirrhotic subjects. J Lab Clin Med 66: 508–516. pmid:5835975
  31. 31. Hotz C, Peerson JM, Brown KH (2003) Suggested lower cutoffs of serum zinc concentrations for assessing zinc status: reanalysis of the second National Health and Nutrition Examination Survey data (1976–1980). Am J Clin Nutr 78: 756–764. pmid:14522734
  32. 32. Age-Related Eye Disease Study Research Group (2002) The effect of five-year zinc supplementation on serum zinc, serum cholesterol and hematocrit in persons randomly assigned to treatment group in the age-related eye disease study: AREDS Report No. 7. J Nutr 132: 697–702. pmid:11925463
  33. 33. Hyun T, Barrett-Connor E, Milne D (2004) Zinc intakes and plasma concentrations in men with osteoporosis: the Rancho Bernardo Study. Am J Clin Nutr 80: 715–721. pmid:15321813
  34. 34. Andriollo-Sanchez M, Hininger-Favier I, Meunier N, Toti E, Zaccaria M, et al. (2005) Zinc intake and status in middle-aged and older European subjects: the ZENITH study. Eur J Clin Nutr 59: S37–41. pmid:16254579
  35. 35. Bureau I, Anderson RA, Arnaud J, Raysiguier Y, Favier AE, et al. (2002)Trace mineral status in post menopausal women: impact of hormonal replacement therapy. J Trace Elem Med Biol 16: 9–13. pmid:11878754
  36. 36. King JC, Hambidge KM, Westcott JL, Kern DL, Marshall G (1994) Daily variation in plasma zinc concentrations in women fed meals at six-hour intervals. J Nutr 124: 508–516. pmid:8145072
  37. 37. Bailey AL, Maisey S, Southon S, Wright AJ, Finglas PM, et al. (1997) Relationships between micronutrient intake and biochemical indicators of nutrient adequacy in a ‘free-living’ elderly UK population. Br J Nutr 77: 225–242. pmid:9135369
  38. 38. Del Corso L, Pastine F, Protti MA, Romanelli AM, Moruzzo D, et al. (2000) Blood zinc, copper and magnesium in aging. A study in healthy home-living elderly. Panminerva Med 42: 273–277. pmid:11294091
  39. 39. Ravaglia G, Forti P, Maioli F, Nesi B, Pratelli L, et al. (2000) Blood micronutrient and thyroid hormone concentrations in the oldest-old. J Clin Endocrinol Metab 85: 2260–2265. pmid:10852460
  40. 40. Rukgauer M, Klein J, Kruse-Jarres JD (1997) Reference values for the trace elements copper, manganese, selenium, and zinc in the serum/plasma of children, adolescents, and adults. J Trace Elem Med Biol 11: 92–98. pmid:9285889
  41. 41. Paik HY, Joung H, Lee JY, Lee HK, King JC, et al. (1999) Serum extracellular superoxide dismutase activity as an indicator of zinc status in humans. Biol Trace Elem Res 69: 45–57. pmid:10383098
  42. 42. Diaz Romero C, Henriquez Sanchez P, Lopez Blanco F, Rodriguez Rodriguez E, Serra Majem L (2002) Serum copper and zinc concentrations in a representative sample of the Canarian population. J Trace Elem Med Biol 16: 75–81. pmid:12195729
  43. 43. Grønli O, Kvamme JM, Friborg O, Wynn R (2013) Zinc deficiency is common in several psychiatric disorders, PLoS ONE 8: e82793. pmid:24367556
  44. 44. Smalbrugge M, Pot AM, Jongenelis L, Gundy CM, Beekman At, et al. (2006) The impact of depression and anxiety on well being, disability and use of health care services in nursing home patients. Int J Geriatr Psychiatry 21: 325–332. pmid:16534766
  45. 45. Rovner BW, German PS, Brant LJ, Clark R, Burton L, et al. (1991) Depression and mortality in nursing homes. JAMA 265: 993–996. pmid:1992213
  46. 46. Siwek M, Dudek D, Paul IA, Sowa-Kucma M, Zieba A, et al. (2009) Zinc supplementation augments efficacy of imipramine in treatment resistant patients: a double blind, placebo-controlled study. J Affect Disord 118: 187–195. pmid:19278731
  47. 47. Maes M, Vandoolaeghe E, Neels H, Demedts P, Wauters A, et al. (1997) Lower serum zinc in major depression is a sensitive marker of treatment resistance and of the immune/inflammatory response in that illness. Biol Psychiatry 42: 349–358. pmid:9276075
  48. 48. Maes M, D’Haese PC, Scharpe S, D’Hondt P, Cosyns P, et al. (1994) Hypozincemia in depression. J Affect Disord 31: 135–140. pmid:8071476
  49. 49. Nowak G, Zieba A, Dudek D, Krosniak M, Szymaczek M, et al. (1999) Serum trace elements in animal models and human depression. Part I. Zinc. Hum Psychopharmacol Clin Exp 14: 83–86.
  50. 50. Amani R, Saeidi S, Nazari Z, Nematpour S (2010) Correlation between dietary zinc intakes and its serum levels with depression scales in young female students. Biol Trace Elem Res 137: 150–158. pmid:20013161
  51. 51. McLoughlin IJ, Hodge JS (1990) Zinc in depressive disorder. Acta Psychiatr Scand 82: 451–453. pmid:2291414
  52. 52. Frederickson CJ, Suh SW, Silva D, Frederickson CJ, Thompson RB (2000) Importance of zinc in the central nervous system: the zinc-containing neuron. J Nutr 130: 1471S—1483S. pmid:10801962
  53. 53. Takeda A, Tamano H, Tochigi M, Oku N (2005) Zinc homeostasis in the hippocampus of zinc-deficient young adult rats. Neurochem Int 46: 221–225. pmid:15670638
  54. 54. Suh SW, Won SJ, Hamby AM, Yoo BH, Fan Y, et al. (2009) Decreased brain zinc availability reduces hippocampal neurogenesis in mice and rats. J Cereb Blood Flow Metab 29: 1579–1588. pmid:19536073
  55. 55. Gray SL, Hanlon JT, Landerman LR, Artz M, Schmader KE, et al. (2003) Is antioxidant use protective of cognitive function in the community-dwelling elderly? Am J Geriatr Pharmacother 1: 3–10. pmid:15555461