Abstract
Context
No studies have examined the association between body habitus and incidence of pituitary adenoma.
Objective
To determine if body mass index (BMI), waist circumference, body somatotype, or height are associated with risk of pituitary adenoma.
Design
Pooled analysis of 3 prospective cohort studies.
Setting
Population-based study.
Participants
Participants of the Nurses’ Health Study (NHS), Nurses’ Health Study II (NHSII), and the Health Professionals Follow-Up Study (HPFS), totaling 284 946 American health professionals.
Exposures
BMI, waist circumference, body somatotype, and height.
Outcome Measures
Self-reported incident pituitary adenoma. Multivariable (MV)-adjusted hazard ratios (HRs) of pituitary adenoma were estimated using Cox proportional hazards models.
Results
During 7 350 156 person-years of follow-up, 387 incident pituitary adenomas were reported. Comparing BMI of ≥30 to <25 kg/m2, higher adult BMI was associated with higher risk of pituitary adenoma (MV HR = 1.74; 95% CI, 1.33-2.28), as was higher maximum adult BMI (MV HR = 1.76; 95% CI, 1.34-2.30), higher waist circumference (MV HR = 1.06; 95% CI, 1.04-1.09 per inch), and higher BMI during early adulthood (at age 18 to 21, MV HR = 2.65; 95% CI, 1.56-4.49). Taller adult height was associated with pituitary adenoma (MV HR = 1.05; 95% CI, 1.01-1.09 per inch). Overall findings were similar in women and men, although power was limited in men (n = 62 cases). Sensitivity analyses demonstrated that the association between adult BMI and pituitary adenoma extended to at least 14 years prior to diagnosis and that the results were not affected when analyses were restricted to participants with similar healthcare utilization.
Conclusion
Higher BMI and waist circumference, from early adulthood to the time of diagnosis, were associated with higher risk of pituitary adenoma.
Keywords: body habitus, body mass index, epidemiology, waist circumference, pituitary adenoma, risk factors
Pituitary adenomas are one of the most common intracranial lesions, with a diagnosed prevalence of 115 per 100 000 population, and an estimated actual prevalence as high as 20% based on autopsy and radiological studies (1-4). These lesions can be broadly divided into functioning and nonfunctioning lesions based on whether or not they secrete active hormones, such as prolactin, growth hormone (GH), adrenocorticotropic hormone (ACTH), or other pituitary hormones, each of which can cause a distinct constellation of clinical symptoms (5). Although histologically benign in almost all cases, pituitary adenomas can cause debilitating headaches, severe endocrine dysfunction, and permanent visual deficits. Hence, identification of patients at high risk for pituitary adenomas remains of interest to practicing primary care physicians, endocrinologists, and neurosurgeons.
Despite their high prevalence, there have been few epidemiological studies of risk factors for pituitary adenomas, and none with serial measurements of body habitus, dietary factors, or other health habits (5). As a result, there are few validated risk factors for pituitary adenoma. Incidence is higher in women than in men, although it is unclear whether these findings are the result of a diagnostic bias or represent any underlying causal relationship (4). Additionally, the duration of the preclinical period of these tumors is unknown, but it is hypothesized to be relatively long, given frequent incidental findings of pituitary adenomas on head imaging and patient retrospective report of the first symptoms that may be attributable to pituitary hyper- or hypofunction, many of which precede diagnosis by several years (5).
Based on evidence that higher body fatness is associated with benign and malignant neoplasms of other sites, our hypothesis was that higher adult BMI and higher adult waist circumference would be associated with higher incidence of pituitary adenoma. We therefore sought to identify the association between body habitus across the life course and risk of pituitary adenoma in 3 large cohorts: the Nurses’ Health Study (NHS), Nurses’ Health Study II (NHSII), and the Health Professionals Follow-Up Study (HPFS).
Methods
Study Participants
The methods of the NHS, NHSII, and HPFS have been described in detail previously (6). NHS was started in 1976 with 121 701 female nurses between the ages of 30 and 55 years; NHSII began in 1989 with 116 686 female nurses between the ages of 25 and 42 years; HPFS began in 1986, with 51 529 male health professionals between the ages of 40 and 75 years. In each cohort, participants completed a baseline questionnaire and subsequent biennial follow-up questionnaires assessed updated information. Questionnaires were expanded across the course of the study to include detailed information on dietary factors, physical activity, and health behaviors, in addition to assessment of health outcomes. Follow-up rates in the cohorts have been higher than 90% (7). The study protocol was approved by the institutional review boards of the Harvard T.H. Chan School of Public Health and Brigham and Women’s Hospital.
Assessment of Body Habitus
At baseline, participants in the 3 cohorts reported their height and weight. Subsequently, weight was included on each biennial questionnaire. A prior validation study has demonstrated a strong correlation between self-reported weight and measured weight (r = 0.97 for both men and women) (8). Body mass index (BMI) was calculated as the weight in kilograms divided by the height in meters squared. To assess early adulthood BMI, participants in NHS were asked in 1980 to report their weight at age 18; this question was included at baseline in NHSII in 1989 (age 18) and HPFS in 1986 (age 21). In the present analyses, we used these values to calculate BMI at age 18 (NHS, NHSII) and at age 21 (HPFS) by assuming all participants had attained their adult height by these ages. This measure of young adult BMI has been validated among women in NHSII, where the correlation between reported current height and measured past height was 0.94 and the correlation between recalled and measured past weight was 0.87 (9). In NHS, waist circumference was assessed in 1986, 1996, and 2000; in NHSII, in 1993 and 2005; and in HPFS, in 1987, 1996, and 2008. The 1988 questionnaire in NHS and HPFS and the baseline questionnaire in NHSII in 1989 asked participants to identify their approximate body shape (somatotype), from a range of 9 options developed by Stunkard et al at age 5, 10, and 20 years (Fig. 1) (10). This retrospective assessment of body habitus during childhood among adult participants has been validated among 181 participants in the Boston-based Third Harvard Growth Study. Among these participants, aged 71 to 76 years, retrospective reports were compared with measured contemporaneous assessments in early life, and Pearson correlation coefficients for women were 0.60 at age 5 and 0.65 at age 10; for men, they were 0.36 at age five and 0.66 at age 10 (11).
Figure 1.
Participants were asked to identify their approximate body type at ages 5, 10, and 20 from the following options on the 1988 questionnaire (NHS, HPFS), and 1989 questionnaire (NHSII).
Identification of Pituitary Adenoma Cases
On each biennial questionnaire, participants were asked to report any disease newly diagnosed by a physician by choosing from a list of common diseases or by writing in their diagnosis if it was not included in the main disease list. Pituitary adenoma was not included as an option in the disease list in any of the cohorts, and all cases were therefore identified by participants writing in their diagnosis on the questionnaires. Participants were considered to have been diagnosed with a pituitary adenoma if they reported any condition consistent with ICD-9 code 227.3 on follow-up questionnaires. By convention, the date of diagnosis of pituitary adenoma was taken to be 12 months prior to the return of the questionnaire. We did not seek medical records to confirm these self-reports.
Covariate Assessment
Smoking status was determined for all participants on each biennial questionnaire and was categorized as never, past, or current.
Additionally, to explore the possibility of diagnostic bias, we used information on healthcare utilization. Specifically, among men, recent healthcare utilization was defined as a physical exam, sigmoidoscopy/colonoscopy, or a rectal exam within the most recent 2 questionnaire cycles. Among women, it was defined as a physical exam, sigmoidoscopy/colonoscopy, or a breast exam within the most recent 2 questionnaire cycles.
Statistical Analyses
We began follow-up time at the date of return of the baseline questionnaire and continued to the date of pituitary adenoma diagnosis, death from another cause, date of return of last questionnaire, or the end of follow-up (June 30, 2014 for NHS; December 31, 2013 for NHSII; December 31, 2017 for HPFS), whichever came first. After excluding those with missing data at baseline, we included 118 991 participants for NHS, 115 031 for NHSII, and 50 924 for HPFS. For analyses using variables that were assessed in later questionnaires, including young adult BMI, waist circumference, body somatotypes, and birthweight, follow-up was calculated from the return of the questionnaire that first asked about that variable. We used Cox proportional hazards models to calculate age-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) to evaluate risk of pituitary adenoma by various measures of body habitus, using months as the time metameter and age and calendar year as stratification variables. Although smoking has not been identified as a risk factor for pituitary adenoma, we included smoking in multivariable-adjusted Cox models as it might be related to likelihood for diagnosis. We also conducted sensitivity analyses adjusting for self-reported race (categorized as White vs non-White) and restricting to those with recent healthcare utilization. Race was first assessed at baseline in HPFS and NHSII, and in 1992 in NHS.
For analyses of BMI, we used the most recent BMI measure available. We carried forward BMI up to 4 years (2 questionnaire cycles) in the case of missing values. If data were still missing, we coded missing data as missing; these individuals did not contribute person-time to the Cox models for periods when they were missing data on a particular covariate. BMI was analyzed both continuously and as a categorical variable according to the standard World Health Organization definition (<25 kg/m2, 25-29.9 kg/m2, ≥30 kg/m2).
To address the potential for reverse causation—the possibility that BMI among pituitary adenoma cases may have changed due to prediagnostic disease—we applied BMI and maximum BMI from 14, 12, 10, 8, 6, 4, and 2 years prior to the current period in separate lagged analyses. This resulted in exclusion of the first 14, 12, 10, 8, 6, 4, and 2 years of follow-up in each case.
For the analyses of waist circumference, we used the most recent report. In the case of missing data, we carried forward previous measurements of waist circumference indefinitely, given the relative infrequency of waist circumference assessment. Waist circumference and height were assessed both continuously and in quintiles.
For the analysis of childhood and adolescent body types at age 5 and 10, we categorized participants into 3 groups that roughly correspond to the categories of BMI we analyzed (categories 1-2, 3-5, 6-9, Fig. 1).
To assess the relative contribution of body habitus at different ages to model fit, we constructed nested Cox proportional hazards models and compared them using a likelihood ratio test.
Analyses were performed separately in each cohort and then combined by fixed effect meta-analysis. A P value < 0.05 was considered statistically significant. All statistical analyses were performed using the SAS 9.4 statistical package (SAS Institute, Cary, NC), and all P values were derived from 2-sided tests. All supplementary tables are available in a data repository (12) and all data are available from the investigators upon reasonable request, as noted on the NHS website, www.nurseshealthstudy.org.
Results
Study Participants
Across 7 350 156 years of follow-up, 387 cases of pituitary adenoma were self-reported by participants (130 in NHS, 195 in NHSII, 62 in HPFS). Baseline characteristics are presented in Table 1. Compared with the overall cohorts, those diagnosed with pituitary adenoma were slightly younger on average than each respective cohort. Pituitary adenoma cases were diagnosed at younger average age in NHSII (40.8 years) than in NHS (61.0 years) or HPFS (59.9 years).
Table 1.
Baseline Characteristics of NHS (1976), NHSII (1989), and HPFS (1986) Participants
| NHS | NHSII | HPFS | ||||
|---|---|---|---|---|---|---|
| Full Cohort (n = 118 991) | Cases (n = 130) | Full Cohort (n = 115 031) | Cases (n = 195) | Full Cohort (n = 50 924) | Cases (n = 62) | |
| Age | 42.9 (7.2) | 41.6 (7.2) | 34.8 (4.7) | 34.3 (4.5) | 54.0 (9.8) | 54.0 (9.0) |
| BMI (kg/m2), median (SD) | 23.8 (4.2) | 24.6 (2.7) | 24.1 (5.1) | 25.0 (3.9) | 25.5 (3.4) | 25.9 (0.9) |
| Smoking status (%) | ||||||
| Never | 43 | 40 | 64 | 74 | 45 | 33 |
| Past | 23 | 25 | 25 | 23 | 42 | 53 |
| Current | 33 | 33 | 10 | 3 | 10 | 10 |
| Missing | 0 | 2 | 1 | 0 | 4 | 4 |
| Median age at diagnosis (years, median, range) | 61.0 (32.1-87.4) | 40.8 (25.7-63.5) | 59.9 (43.0-84.3) | |||
| Time to diagnosis from baseline (years, median, range) | 19.0 (0.6-36.9) | 5.3 (0.3-24.3) | 4.8 (0.3-23.7) |
Abbreviations: BMI, body mass index; HPFS, Health Professionals Follow-Up Study; NHS, Nurses’ Health Study; NHSII, Nurses’ Health Study II.
Adult BMI and Waist Circumference
Overall, higher adult BMI was associated with higher risk of pituitary adenoma (Table 2). Each additional 5 kg/m2 of BMI was associated with a 26% higher risk of pituitary adenoma (95% CI, 17%-37%); compared with those with BMI <25 kg/m2, those with BMI ≥30 kg/m2 had a 74% higher risk of pituitary adenoma (multivariable [MV] HR = 1.74; 95% CI, 1.33-2.28). Findings were similar for maximum BMI (MV HR = 1.76; 95% CI, 1.34-2.30 comparing maximum BMI ≥30 to <25 kg/m2; MV HR = 1.24; 95% CI, 1.15-1.33 per 5 kg/m2). Higher adult waist circumference was also associated with higher risk of pituitary adenoma. Compared with those in the lowest quintile of waist circumference, those in the highest quintile had a 130% higher risk of pituitary adenoma (HR = 2.30; 95% CI, 1.33-3.98) and each additional inch of waist circumference was associated with a 6% higher risk of pituitary adenoma (95% CI, 4%-9%).
Table 2.
Risk of Pituitary Adenoma in NHS, NHSII, and HPFS by Measures of Body Habitus
| Casesa | HRbc | 95%CI | MV HRcd | 95%CI | ||
|---|---|---|---|---|---|---|
| BMI | <25 | 200 | Ref. | Ref. | ||
| 25–29.9 | 122 | 1.56 | 1.22–1.98 | 1.56 | 1.22–1.98 | |
| ≥30 | 64 | 1.74 | 1.33–2.28 | 1.74 | 1.33–2.28 | |
| Per 5 kg/m2 | 386 | 1.27 | 1.17–1.37 | 1.26 | 1.17–1.37 | |
| Maximum BMI | <25 | 142 | Ref. | Ref. | ||
| 25–29.9 | 145 | 1.66 | 1.29–2.12 | 1.66 | 1.30–2.13 | |
| ≥30 | 99 | 1.75 | 1.34–2.30 | 1.76 | 1.34–2.30 | |
| Per 5 kg/m2 | 386 | 1.24 | 1.15–1.34 | 1.24 | 1.15–1.33 | |
| Waist circumference | Quintile 1 | 19 | Ref. | Ref. | ||
| Quintile 2 | 31 | 1.10 | 0.59–2.04 | 1.10 | 0.59–2.03 | |
| Quintile 3 | 33 | 1.45 | 0.79–2.66 | 1.44 | 0.78–2.65 | |
| Quintile 4 | 42 | 1.72 | 0.96–3.06 | 1.72 | 0.96–3.06 | |
| Quintile 5 | 48 | 2.32 | 1.34–4.01 | 2.30 | 1.33–3.98 | |
| Per inch | 173 | 1.06 | 1.04–1.09 | 1.06 | 1.04–1.09 | |
| Baseline BMIe | <25 | 228 | Ref. | Ref. | ||
| 25–29.9 | 112 | 1.47 | 1.15–1.88 | 1.47 | 1.15–1.88 | |
| ≥30 | 44 | 1.42 | 1.03–1.97 | 1.43 | 1.03–1.98 | |
| Per 5 kg/m2 | 384 | 1.21 | 1.09–1.33 | 1.21 | 1.09–1.33 | |
| Height | Quintile 1 | 64 | Ref. | Ref. | ||
| Quintile 2 | 78 | 1.12 | 0.80–1.57 | 1.13 | 0.80–1.57 | |
| Quintile 3 | 80 | 1.27 | 0.91–1.77 | 1.28 | 0.92–1.78 | |
| Quintile 4 | 85 | 1.21 | 0.87–1.68 | 1.21 | 0.87–1.68 | |
| Quintile 5 | 80 | 1.39 | 1.00–1.93 | 1.39 | 1.00–1.93 | |
| Per inch | 387 | 1.05 | 1.01–1.09 | 1.05 | 1.01–1.09 | |
| Young adult BMIf | <25 | 295 | Ref. | Ref. | ||
| 25–29.9 | 41 | 1.31 | 0.87–1.68 | 1.21 | 0.87–1.68 | |
| ≥30 | 15 | 2.58 | 1.53–4.38 | 2.65 | 1.56–4.49 | |
| Per 5 kg/m2 | 351 | 1.25 | 1.09–1.44 | 1.26 | 1.10–1.45 | |
| Age 20 somatotype | 1–2 | 97 | Ref. | Ref. | ||
| 3–5 | 176 | 0.91 | 0.71–1.17 | 0.92 | 0.71–1.18 | |
| 6–9 | 18 | 2.05 | 1.23–3.43 | 2.10 | 1.26–3.51 | |
| Age 10 somatotype | 1–2 | 149 | Ref. | Ref. | ||
| 3–5 | 128 | 1.00 | 0.79–1.27 | 1.01 | 0.79–1.28 | |
| 6–9 | 12 | 1.08 | 0.60–1.96 | 1.10 | 0.61–1.99 | |
| Age 5 Somatotype | 1–2 | 168 | Ref. | Ref. | ||
| 3–5 | 114 | 1.01 | 0.80–1.29 | 1.02 | 0.80–1.30 | |
| 6–9 | 6 | 1.03 | 0.45–2.39 | 1.03 | 0.44–2.38 | |
| Birthweight | <7 lbs. | 59 | Ref. | Ref. | ||
| 7–8.5 lbs. | 95 | 1.30 | 0.94–1.81 | 1.30 | 0.94–1.80 | |
| >8.5 lbs. | 34 | 1.58 | 1.02–2.43 | 1.57 | 1.01–2.42 | |
| Smoking Status | Never | 214 | Ref. | |||
| Past | 122 | 1.07 | 0.84–1.36 | |||
| Current | 37 | 0.78 | 0.54–1.12 |
Abbreviations: BMI, body mass index; HR, hazard ratio
aCases may not sum to total due to missing values.
bAdjusted for age and cohort (which adjusts for sex)
cCalculated by fixed effect meta-analysis of all 3 cohorts.
dAdditionally adjusted for smoking status (never vs. past vs. current).
eBaseline is 1986 in HPFS, 1976 in NHS, and 1989 in NHSII.
fAge 18 in NHS and NHSII, age 21 in HPFS. Abbreviations: BMI, body mass index; HPFS, Health Professionals Follow-Up Study; HR, hazard ratio; MV, multivariable; NHS, Nurses’ Health Study; NHSII, Nurses’ Health Study II;
Findings were consistent overall in both women (n = 325) and men (n = 62), but analyses restricted to men had substantially lower power due to smaller case counts (Table 3). Compared with those with BMI <25 kg/m2, those with BMI ≥30 kg/m2 had significantly higher risk of pituitary adenoma among women (MV HR = 1.77; 95% CI, 1.33-2.34) but not men (MV HR = 1.45; 95% CI, 0.56-3.78). Higher waist circumference was significantly associated with higher risk of pituitary adenoma in both women (MV HR = 1.06; 95% CI, 1.03-1.09 per inch) and men (MV HR = 1.09; 95% CI, 1.01-1.17 per inch). Findings diverged for early adulthood BMI (MV HR = 1.32; 95% CI, 1.14-1.52 per 5 kg/m2 for women; MV HR = 0.81; 95% CI, 0.51-1.30 per 5 kg/m2 for men), but cases were sparse among heavier categories for men (eg, no cases with early adulthood BMI ≥30 kg/m2).
Table 3.
Risk of Pituitary Adenoma in NHS, NHSII, and HPFS by Measures of Body Habitus, Stratified by Sex
| Women (n = 325) | Men (n = 62) | ||||||
|---|---|---|---|---|---|---|---|
| Casesa | MV HRbc | 95%CI | Casesa | MV HRb | 95%CI | ||
| BMI | <25 | 185 | Ref. | 15 | Ref. | ||
| 25–29.9 | 82 | 1.45 | 1.11–1.89 | 40 | 2.25 | 1.24–4.09 | |
| ≥30 | 58 | 1.77 | 1.33–2.34 | 6 | 1.45 | 0.56–3.78 | |
| Per 5 kg/m2 | 325 | 1.27 | 1.17–1.37 | 61 | 1.22 | 0.90–1.66 | |
| Maximum BMI | <25 | 130 | Ref. | 12 | Ref. | ||
| 25–29.9 | 103 | 1.55 | 1.19–2.03 | 42 | 2.46 | 1.29–4.70 | |
| ≥30 | 92 | 1.77 | 1.34–2.35 | 7 | 1.56 | 0.60–4.01 | |
| Per 5 kg/m2 | 325 | 1.24 | 1.15–1.34 | 61 | 1.17 | 0.86–1.59 | |
| Waist circumference | Quintile 1 | 18 | Ref. | 1 | Ref. | ||
| Quintile 2 | 26 | 0.96 | 0.50–1.83 | 5 | 4.69 | 0.55–40.24 | |
| Quintile 3 | 22 | 1.16 | 0.61–2.20 | 11 | 13.18 | 1.69–102.62 | |
| Quintile 4 | 27 | 1.43 | 0.78–2.62 | 15 | 13.20 | 1.73–100.62 | |
| Quintile 5 | 38 | 2.06 | 1.17–33.64 | 10 | 9.89 | 1.26–77.78 | |
| Per inch | 131 | 1.06 | 1.03–1.09 | 42 | 1.09 | 1.01–1.17 | |
| Baseline BMId | <25 | 212 | Ref. | 16 | Ref. | ||
| 25–29.9 | 71 | 1.31 | 1.00–1.72 | 41 | 2.49 | 1.39–4.44 | |
| ≥30 | 42 | 1.49 | 1.07–2.08 | 2 | 0.66 | 0.15–2.88 | |
| Per 5 kg/m2 | 325 | 1.22 | 1.10–1.34 | 59 | 1.08 | 0.75–1.56 | |
| Height | Quintile 1 | 56 | Ref. | 8 | Ref. | ||
| Quintile 2 | 63 | 1.09 | 0.76–1.58 | 15 | 1.28 | 0.54–3.04 | |
| Quintile 3 | 67 | 1.25 | 0.88–1.79 | 13 | 1.46 | .60–3.55 | |
| Quintile 4 | 70 | 1.24 | 0.87–1.77 | 15 | 1.02 | 0.43–2.43 | |
| Quintile 5 | 69 | 1.42 | 1.00–2.02 | 11 | 1.19 | 0.47–2.98 | |
| Per inch | 325 | 1.05 | 1.00–1.09 | 62 | 1.05 | 0.95–1.15 | |
| Young adult BMIe | <25 | 248 | Ref. | 47 | Ref. | ||
| 25–29.9 | 30 | 1.40 | 0.96–2.05 | 11 | 0.78 | 0.40–1.51 | |
| ≥30 | 15 | 2.65 | 1.56–4.49 | 0 | - | ||
| Per 5 kg/m2 | 293 | 1.32 | 1.14–1.52 | 58 | 0.81 | 0.51–1.30 | |
| Age 20 somatotype | 1–2 | 85 | Ref. | 12 | Ref. | ||
| 3–5 | 159 | 0.97 | 0.74–1.27 | 17 | 0.59 | 0.28–1.25 | |
| 6–9 | 17 | 2.30 | 1.35–3.91 | 1 | 0.55 | 0.07–4.31 | |
| Age 10 somatotype | 1–2 | 131 | Ref. | 18 | Ref. | ||
| 3–5 | 119 | 1.04 | 0.81–1.33 | 9 | 0.75 | 0.34–1.68 | |
| 6–9 | 9 | 1.18 | 0.60–2.32 | 3 | 0.87 | 0.25–3.01 | |
| Age 5 somatotype | 1–2 | 149 | Ref. | 19 | Ref. | ||
| 3–5 | 106 | 1.05 | 0.82–1.35 | 8 | 0.74 | 0.32–1.69 | |
| 6–9 | 3 | 0.71 | 0.22–2.22 | 3 | 1.59 | 0.46–5.47 | |
| Birthweight | <7 lbs. | 58 | Ref. | 1 | Ref. | ||
| 7–8.5 lbs. | 88 | 1.27 | 0.91–1.76 | 7 | 3.75 | 0.46–30.65 | |
| >8.5 lbs. | 30 | 1.51 | 0.97–2.35 | 4 | 4.24 | 0.47–38.31 | |
| Smoking status | Never | 192 | Ref. | 22 | Ref. | ||
| Past | 85 | 0.94 | 0.72–1.23 | 37 | 1.81 | 1.06–3.09 | |
| Current | 34 | 0.77 | 0.53–1.14 | 3 | 0.81 | 0.24–2.71 |
Abbreviations: BMI, body mass index; HPFS, Health Professionals Follow-Up Study; HR, hazard ratio; MV, multivariable; NHS, Nurses’ Health Study; NHSII, Nurses’ Health Study II.
aCases may not sum to total due to missing values.
bAdjusted for age and smoking status (never vs. past vs. current).
cCalculated by fixed effect meta-analysis of NHS and NHSII.
dBaseline is 1986 in HPFS, 1976 in NHS, and 1989 in NHSII.
eAge 18 in NHS and NHSII, age 21 in HPFS.
Positive associations between higher adult BMI and pituitary adenoma risk persisted through lagged analyses of up to 14 years (Table 4). After excluding the first 14 years of follow-up and the 257 cases that occurred during that period, adult BMI (MV HR = 1.81; 95% CI, 1.14-2.86 comparing BMI ≥30 to <25 kg/m2; MV HR = 1.27; 95% CI, 1.10-1.46 per 5 kg/m2) and maximum adult BMI (MV HR = 2.09; 95% CI, 1.32-3.29 comparing maximum BMI ≥30 to <25 kg/m2; MV HR = 1.25; 95% CI, 1.09-1.44 per 5 kg/m2) were each associated with higher risk of pituitary adenoma.
Table 4.
Risk of Pituitary Adenoma in HPFS, NHS, and NHSII by Measures of Body Habitus, Lagged Analyses
| 14-Year Lag | 12-Year Lag | 10-Year Lag | 8-Year Lag | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Casesa | MV HRbc | 95%CI | Casesa | MV HRbc | 95%CI | Casesa | MV HRbc | 95%CI | Casesa | MV HRbc | 95%CI | ||
| BMI | <25 | 61 | Ref. | 68 | Ref. | 82 | Ref. | 83 | Ref. | ||||
| 25–29.9 | 40 | 1.37 | 0.91–2.06 | 43 | 1.23 | 0.82–1.85 | 56 | 1.40 | 0.98–2.00 | 64 | 1.53 | 1.08–2.17 | |
| ≥30 | 28 | 1.81 | 1.14–2.86 | 33 | 1.73 | 1.13–2.64 | 39 | 1.70 | 1.15–2.51 | 47 | 1.91 | 1.32–2.78 | |
| Per 5 kg/m2 | 129 | 1.27 | 1.10–1.46 | 144 | 1.22 | 1.06–1.40 | 177 | 1.22 | 1.07–1.38 | 194 | 1.27 | 1.13–1.42 | |
| Maximum BMI | <25 | 52 | Ref. | 49 | Ref. | 79 | Ref. | 77 | Ref. | ||||
| 25–29.9 | 46 | 1.70 | 1.13–2.55 | 49 | 1.42 | 0.96–2.11 | 60 | 1.50 | 1.05–2.13 | 66 | 1.48 | 1.04–2.10 | |
| ≥30 | 31 | 2.09 | 1.32–3.29 | 36 | 1.88 | 1.23–2.89 | 38 | 1.74 | 1.18–2.58 | 51 | 1.82 | 1.26–2.63 | |
| Per 5 kg/m2 | 129 | 1.25 | 1.09–1.44 | 144 | 1.22 | 1.07–1.39 | 177 | 1.20 | 1.06–1.36 | 194 | 1.24 | 1.11–1.38 | |
| 6-Year Lag | 4-Year Lag | 2-Year Lag | No Lag | ||||||||||
| Casesa | MV HRbc | 95%CI | Casesa | MV HRbc | 95%CI | Casesa | MV HRbc | 95%CI | Casesa | MV HRbc | 95%CI | ||
| BMI | <25 | 91 | Ref. | 106 | Ref. | 132 | Ref. | 200 | Ref. | ||||
| 25–29.9 | 77 | 1.61 | 1.15–2.24 | 98 | 1.75 | 1.31–2.35 | 111 | 1.66 | 1.27–2.18 | 122 | 1.56 | 1.22–1.98 | |
| ≥30 | 55 | 1.94 | 1.37–2.74 | 60 | 1.80 | 1.30–2.50 | 71 | 1.80 | 1.33–2.43 | 64 | 1.74 | 1.33–2.28 | |
| Per 5 kg/m2 | 223 | 1.27 | 1.14–1.40 | 264 | 1.25 | 1.14–1.38 | 314 | 1.25 | 1.14–1.36 | 386 | 1.26 | 1.17–1.37 | |
| Maximum BMI | <25 | 82 | Ref. | 97 | Ref. | 119 | Ref. | 142 | Ref. | ||||
| 25–29.9 | 80 | 1.61 | 1.15–2.24 | 98 | 1.64 | 1.21–2.22 | 115 | 1.66 | 1.26–2.20 | 145 | 1.66 | 1.30–2.13 | |
| ≥30 | 61 | 1.93 | 1.37–2.73 | 69 | 1.81 | 1.31–2.50 | 80 | 1.81 | 1.34–2.44 | 99 | 1.76 | 1.34–2.30 | |
| Per 5 kg/m2 | 223 | 1.26 | 1.14–1.39 | 264 | 1.24 | 1.13–1.36 | 314 | 1.24 | 1.14–1.35 | 386 | 1.24 | 1.15–1.33 |
Abbreviations: BMI, body mass index; HPFS, Health Professionals Follow-Up Study; MV, multivariable; NHS, Nurses’ Health Study; NHSII, Nurses’ Health Study II.
aCases may not sum to total due to missing values.
bAdjusted for age, cohort (which adjusts for sex), smoking status (never vs. past vs. current).
cCalculated by fixed effect meta-analysis of all 3 cohorts.
Adult Height
Taller adult height was associated with a higher risk of pituitary adenoma. Each additional inch of adult height was associated with 5% higher risk of pituitary adenoma (MV HR = 1.05; 95% CI, 1.01-1.09). These findings were similar in women (MV HR = 1.05; 95% CI, 1.00-1.09 per inch) and men (MV HR = 1.05; 95% CI, 0.95-1.15 per inch).
Early Adulthood BMI
Higher BMI at age 18 (in NHS and NHSII) and at age 21 (in HPFS) was associated with higher risk of pituitary adenoma. Compared to a young adult BMI <25 kg/m2, a young adult BMI of ≥30 kg/m2 was associated with a 165% higher risk of pituitary adenoma (95% CI, 56%-349%), and each additional 5 kg/m2 of young adult BMI was associated with a 26% higher risk of pituitary adenoma (MV HR = 1.26; 95% CI, 1.10-1.45).
Childhood Body Somatotype
There was no evidence of an association between body somatotype at age 5 or at age 10 and incidence of pituitary adenoma (MV HR = 1.03; 95% CI, 0.44-2.38 comparing 6-9 to 1-2 at age 5; MV HR = 1.10; 95% CI, 0.61-1.99 comparing 6-9 to 1-2 at age 10). Larger body somatotype at age 20 was associated with higher risk of pituitary adenoma (MV HR = 2.10; 95% CI, 1.26-3.51 comparing 6-9 to 1-2 at age 20), consistent with the findings for young adult BMI.
Birthweight
Higher birthweight was associated with higher risk of pituitary adenoma. Compared to those who were <7 lbs. at birth, those >8.5 pounds had significantly higher risk of pituitary adenoma (HR = 1.57; 95% CI, 1.01-2.42).
Likelihood Ratio Tests
The results of likelihood ratio tests on nested models suggested that addition of birthweight did not improve model fit in any of the cohorts (12). This implies that the observed association for birthweight was mediated by adult BMI. Addition of young adult BMI did not significantly improve model fit in NHS and HPFS, but adding young adult BMI improved fit in NHSII (P = 0.01 in MV model).
Sensitivity Analyses
Adjustment for race did not materially change the overall results (data not shown). Higher adult BMI (HR = 1.58; 95% CI, 1.15-2.17 comparing BMI ≥30 kg/m2 to <25 kg/m2) and higher maximum BMI (HR = 1.70; 95% CI, 1.23-2.34 comparing maximum BMI ≥30 kg/m2 to <25 kg/m2) were each associated with higher risk of pituitary adenoma after adjustment for race. Taller height also remained significantly associated with higher risk of pituitary adenoma (HR = 1.05; 95% CI, 1.00-1.09 per inch).
After restricting the analysis to participants with recent healthcare utilization, the overall findings were unchanged (12). Higher adult BMI (HR = 1.71; 95% CI, 1.27-2.30 comparing BMI ≥30 kg/m2 to <25 kg/m2) and higher maximum BMI (HR = 1.75; 95% CI, 1.30-2.36 comparing maximum BMI ≥30 kg/m2 to <25 kg/m2) were each associated with higher risk of pituitary adenoma.
Discussion
Overall, our findings suggest that higher adult adiposity, as reflected in higher BMI and waist circumference, is associated with increased risk of pituitary adenoma. Findings were similar when we used maximum adult BMI, most recent BMI, or BMI extending as far back as the baseline questionnaire (1976 in NHS, 1986 in HPFS, and 1989 in NHSII), as well as early adulthood (age 18 in NHS and NHSII, age 21 in HPFS). Taken together, these findings suggested a risk that was nearly twice as high among those with obesity (≥30 kg/m2) compared to those with a healthy weight (<25 kg/m2).
Strengths of our study include the high-quality data from which we drew our inferences. The NHS, NHSII, and HPFS are large, prospective, validated cohort studies that have been used to study a variety of exposures and health outcomes. In total, we accrued over 8 million person-years of follow-up with detailed responses from participants. Assessing each exposure multiple times allowed us to perform lagged analyses, a unique opportunity that eliminates the risk of reverse causation bias driving the findings of the study. This is particularly relevant in the case of pituitary adenoma, given that many patients, especially those ultimately diagnosed with Cushing’s disease, acromegaly, or hypopituitarism, often experience significant weight gain prediagnostically.
One limitation of the study is that the exposures involved, including BMI, waist circumference, and height, as well as diagnoses of pituitary adenoma, were self-reported by participants. The cohorts were designed with nurses and health professionals as participants explicitly because these individuals can provide accurate recall of medical conditions. We have previously documented the accuracy of recall of a wide range of medical conditions (including cancer, hypertension, diabetes, and many others) in these cohorts, by comparing self-report with medical records (6, 13-18). Furthermore, prior evidence suggests that across 7 350 156 person-years of follow-up, we should have expected approximately 191 to 543 cases of pituitary adenoma (19, 20), similar to our observed 387 cases. This suggests that self-report may not be a major limitation of our data; however, without medical records, we cannot classify the tumor type (eg, functioning vs nonfunctioning). Based on the overall epidemiology of pituitary adenomas in the United States, the majority of these lesions, particularly among women, are likely prolactinomas, which make up 30% to 60% of prevalent pituitary adenomas (5). In addition, some lesions are likely incidentally discovered, as asymptomatic lesions can account for as much as 10% of diagnosed adenomas (2, 4, 21).
Notably, the majority of follow-up time (86%) and cases (84%) in this study are among females, not males, due to the longer follow-up and larger size of the NHS studies, as well as the differing age distributions of the cohorts; therefore, the pooled results are driven mainly by findings among females. In particular, null findings among men should be interpreted with caution given low power and overall similar hazard ratio estimates compared to women, despite wide confidence intervals. In addition, data collection and study participation across the cohorts occurred at different times, beginning in 1976 with women and later, in 1986, with men, which may result in temporal differences in the sex-stratified analyses. Additional limitations include the possibility of residual confounding. Given that few risk factors for pituitary adenoma have been identified, we adjusted empirically for smoking status and race, given evidence that these play a confounding role in studies of BMI and cancers of other sites, but unknown confounders remain possible. Lastly, the participants in these cohorts are overwhelmingly White, a major limitation that may affect the generalizability of our findings.
Our hypothesis that participants with higher adult BMI and waist circumference would be at higher risk for pituitary adenoma was based on limited evidence. Few risk factors for pituitary adenoma have been identified, and most studies reported in the literature are retrospective case-control studies. A 2009 case-control study of 506 pituitary adenoma patients screened a range of possible exposures, identifying surgically induced menopause, young age of menopause, and young age at first childbirth as associated with pituitary adenoma (22). Use of oral contraceptives has also been investigated in several case-control studies, with mostly null results (23-26). No studies have examined the association between body habitus and pituitary adenoma incidence, but higher body weight is associated with pancreatic and postmenopausal breast cancers, among others (27-30). In addition to these associations with malignant lesions, recent evidence also suggests that higher adiposity (as imperfectly measured by BMI) may be related to higher incidence of histologically benign lesions, including thyroid nodules (31-33) and uterine leiomyomas (34-36), which may be more similar in etiology to pituitary adenomas. The findings reported here appear to be stronger than the associations reported between BMI and thyroid nodules (OR = 1.16 per 5 kg/m2; P = 0.008) (31), but similar to those for uterine leiomyomas (OR = 1.2; P = 0.03 among premenopausal women) (34).
Hypothesized mechanisms for these relationships include the possibility that circulating estrogens, produced at higher levels by adipose tissue, may contribute to the growth or genesis of these lesions (31), or that higher levels of systemic or site-specific inflammation among those with obesity may play a role (27, 30, 37). Disorders of glucose and lipid metabolism related to obesity have also been linked to tumorigenesis (38-40). Based on these findings, we hypothesized that those with higher body fatness, as measured by BMI and waist circumference, would be at higher risk of pituitary adenoma.
Our findings confirmed our hypotheses and suggest that higher BMI, higher waist circumference, and larger body type as early as young adulthood are associated with increased incidence of pituitary adenoma. Several other important findings emerged from our study. First, in lagged analyses, associations between higher BMI and pituitary adenoma risk extended at least 14 years prior to diagnosis, showing that reverse causation (ie, preclinical weight gain induced by undiagnosed pituitary adenoma) is an unlikely cause of our findings. Additionally, analyses of early adulthood BMI and baseline BMI also showed significant associations between higher BMI and pituitary adenoma incidence. The baseline BMI measurement occurred a median of 5 years (in NHSII and HPFS) or 19 years (in NHS) prior to diagnosis, and case diagnosis occurred a median of 43 years (in NHS), 23 years (in NHSII), and 39 years (in HPFS) after the reported early adulthood BMI. Although the preclinical period for these tumors may be long, it is unlikely that it extends multiple decades on average, or that preclinical tumor would cause weight gain so long before diagnosis. There was no association between childhood somatotype at age 5 and 10 and later incidence of pituitary adenoma, but there was an association between somatotype at age 20 and all later measures of body habitus, suggesting that the association between body habitus and pituitary adenoma incidence may begin around puberty. Additionally, we identified no consistent associations between smoking behavior and pituitary adenoma incidence, and minimal evidence of confounding of the association between body habitus and pituitary adenoma by smoking status.
Diagnostic bias is a possible alternative explanation for our findings. It is possible that participants with obesity are subjected to closer medical scrutiny, due to comorbid conditions, which may lead to diagnosis of incidental pituitary lesions that would otherwise remain undiagnosed (41). For example, participants with obesity may have thyroid or other endocrine function measured, which may lead to further workup, including pituitary imaging, in the setting of an abnormal test result. On the other hand, it has been demonstrated that patients with obesity are subject to discrimination and stigma that may result in reduced utilization of medical care (42-44). To examine this issue, we conducted a sensitivity analysis restricted only to participants with recent healthcare utilization, and the results were materially unchanged. Although the possibility remains that a diagnostic bias is present even among this restricted population, it seems unlikely that such a bias would drive the overall findings, particularly since all participants were health professionals with access to medical care.
The finding that higher birthweight is associated with later incidence of pituitary adenoma is consistent with previous studies of thyroid cancer, breast cancer, and glioma, which all suggested higher risk of cancer with higher birthweight (45-49). While it is possible that birthweight has an independent effect on later cancer risk, it is also possible that birthweight is associated with later risk due to its association with adult BMI. Our finding that addition of birthweight to models already including adult BMI did not improve model fit provides further evidence that postpubertal BMI may be the major factor associated with pituitary adenoma incidence.
Overall, our findings suggest an association between higher adult body weight and risk of pituitary adenoma. Given the lack of prior research in this area and despite some limitations, our findings provide a promising new area of research into etiologic risk factors for pituitary adenoma. Further investigation of these findings would help to ascertain whether our findings are generalizable to other populations. Subtype information on pituitary adenoma type, particularly functional status of the tumor and associated presenting symptoms, such as hypopituitarism, would help determine whether associations with body habitus or preclinical weight changes vary by disease type.
Conclusion
Higher BMI and waist circumference, from early adulthood up to the time of diagnosis, were associated with higher risk of pituitary adenoma. Sensitivity analyses suggested that reverse causation and diagnostic bias were unlikely causes of these findings.
Acknowledgments
We would like to thank the participants and staff of the Nurses’ Health Study, the Nurses’ Health Study II, and the Health Professionals Follow-Up Study for their valuable contributions. The authors assume full responsibility for analyses and interpretation of these data.
Financial Support: National Institutes of Health (NIH) PO1 CA87969, U01 CA167552, UM1 CA186107, U01 CA176726, UM1 CA167552, R37 HD019938 (UBK), F30 CA235791 (DJC).
Glossary
Abbreviations
- ACTH
adrenocorticotropic hormone
- BMI
body mass index
- GH
growth hormone
- HPFS
Health Professionals Follow-Up Study
- NHS
Nurses’ Health Study
- NHS II
Nurses’ Health Study II
Additional Information
Disclosures: The authors have nothing to disclose.
Data Availability
All supplementary tables are available in a data repository (12) and all data are available from the investigators upon reasonable request, as noted on the NHS website, www.nurseshealthstudy.org.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
All supplementary tables are available in a data repository (12) and all data are available from the investigators upon reasonable request, as noted on the NHS website, www.nurseshealthstudy.org.