Correlations between Barometric Pressure and Child Birth Rates - Article Example

www.allwriting.net Sumanta Sanyal Dated: 12/10/06 Tulsa, Oklahoma, USA: Correlations between Barometric Pressure and Child Birth Rates (1980-1995) – An Analysis Abstract It is a well-known fact that there are many societies and communities, some primitive and others quite modern, as well as individuals across the globe that firmly believe that the moon, through its periodic lunar cycles, influences fertility rates and conception. There is also prevalent across the globe some of those who believe that women conceive more when the barometer drops. While the lunar theory has been propagated through a large body of literature the other theory, the pressure one, has no written records. It is also notable that the lunar theory has scientific proponents that believe that human biorhythms are linked to weather changes, a modern enough and accepted belief, and that weather changes, in turn, are influenced by lunar, solar and star cycles (Whole Earth Forecaster, Item 27, 2006). Nevertheless, the theory on the association of barometric pressure with human fertility is accepted as one that this paper deems worthwhile to investigate. The paper first undertakes a literature review that reveals that many climatic and weather variables such as temperature, precipitation, humidity and others affect, both adversely and beneficially, human physiology and psychology. It also finds that fertility and birth rates are definitively associated with these climate and weather variables. There are also a number of factors associated with these variables that either enhance or diminish their effective strengths on humans. The paper includes these legitimate observations of reputed scientists. Nevertheless, the paper does not find any association between birth rates and fertility with barometric pressure in available literature. Thus, it is decided that it will conduct an individual study to find if barometric pressure can really be associated in any manner with birth rates and fertility. The barometric pressure for Tulsa, Oklahoma, USA, for the period 1990-2000 is derived from the ‘National Oceanic and Atmospheric Association’ (NOAA) together with the number of births, the birth rates and the fertility rates for the same period from the ‘Oklahoma State Department of Health’. The birth rate is accepted as the most likely variable to check against the barometric pressure as it is detrended against population fluxes in the period under study. The methodology decided upon is a simple Linear Correlation and Regression test at 5% significance level. This is so because there is no literature to support a view that there is at all any correlation between the atmospheric and human variables. It is decided that if any significant correlation does show in this test a more detailed test shall be conducted to study more intricate aspects of the relationship. The initial Pearson’s Correlation test shows that the values for (Coefficient of correlation) at .326 do not specify any significant relationship between the atmospheric and human variables. The (Coefficient of determination) value at .106 reinforces this and the conclusion arrived at is definitely, there is no correlation between barometric pressure and human conception and birth rates. The .95 confidence interval is also large for and this also signifies that any change in sample sizes will not significantly affect the correlationship results. The paper thus definitely concludes that the association between barometric pressure and human birth rates is an old wives’ tale and should be treated as such. Introduction The principal purpose of this paper is to investigate whether there is any scientific basis to the general belief that women conceive more, hence birth rates increase, when the barometric pressure is high. To introduce this subject of association of elements of climate and weather, henceforth called variables, historically the paper finds that there is a widely accepted belief in many primitive as well as modern societies, also adhered to by many individuals living all across the globe, that women conceive more, or their fertility increases, when the moon is at a certain position in the sky. This belief is reinforced when the paper finds Francesa Naish in her book ‘The Lunar Cycle’, pages 19-20, telling us – “Over and over in clinical use of the lunar phase cycle instances have occurred where this cycle seemingly explains otherwise puzzling phenomenon” (Derived from: Lunar Fertility History, 2006). Thus, a written account of this belief, one of humankind’s oldest, is available. The paper finds though that the other belief that barometric pressure can be associated with feminine fertility is more difficult to account for academically. Thus, it is assumed that the belief, like many others similar to it, exists beyond reach of the print media and is propagated mostly by word of mouth. This being said the paper now mores on to investigate whether there is any scientific basis for associating human physiology with climate and weather variables and finds that there definitely is substantive reason to believe so. Human Physiology and Climate and Weather Variables It is hypothecated by experts that all climate and weather variables affect human health in some way. This may be directly by adverse changes in physiology or indirectly by creating friendly environments for disease-causing organisms or their vectors (White and Hertz-Picciotto, 1985). The purpose of this paper concerns direct effects that adversely affect human physiology and often, subsequently, through physiological agents like hormones, human psychology as well. Presently, to introduce this hypothetical element in the interaction between humans and the dynamisms in their immediate environment, the essay shall first assess some conclusions that have already changed the hypothetical nature of this subject to scientific fact. It is well-established that certain elements of weather, in dynamism, are directly related to changes in human physiological and psychological functions. Some of these dynamisms have been known to change birth rates and sperm counts (Kalkstein and Valimont, 1987). Unfortunately, there is no literature that pinpoints barometric pressure as one such particular dynamism that affects birth rates. Thus, the paper has to investigate that on its own. Nevertheless, many mortality and morbidity factors are much enhanced by short and long term weather patterns either directly through physiological changes or through creating friendly conditions for disease-causing organisms or their vectors. The greatest number of studies on the effects of these dynamisms has been conducted on dynamics of temperature. Both extreme eat and cold palpably increase morbidity and mortality rates. The particular temperature at which morbidities and, often, mortalities initiate may be taken to be the threshold temperature and it varies from region to region. Thus, within the same country, as the USA, high mortality rates in the milder southern states may be initiated at C (Atlanta threshold) while in the colder northern states such may occur at -C (Philadelphia threshold) (Kalkstein and Valimont, 1987). The thresholds may differ more radically between countries – tropical and temperate ones. Also, one other element to affection by temperature is that stated by Katayama and Momiyama-Sakamoto (1970). Their studies have disclosed that regions with high seasonal variations in the temperature range have higher related mortality rates than regions with less extreme seasonal variations (Kalkstein and Valimont, 1987). There is some amount of controversy over what period, daily, weekly, seasonally, most affects mortality. Some like Sakamoto and Katayama (1971) postulate that, mostly, monthly and annual large variations in temperature affect mortality rates most while others like Kalkstein and Davis (1985) hold that daily extreme fluctuations can increase mortality rates by over 50% in some US cities (Kalkstein and Valimont, 1987). It must be noted that, here, till now, temperature change signifies the higher end – heat. Kalkstein and Valimont (1987) find that hot weather has higher impact than cold. High variations in heat, whether in the short or long term, induces the human body to neutralize the thermal stress with increased blood supply to the peripheral regions so that heat loss through the skin is facilitated. This increased blood pressure not only affects morbidity through heart dysfunctions but also through many other physiological dysfunctions. These may subsequently be converted to mortal conditions. Kalkstein and Valimont (1987) also note, on the other hand, that very short term temperature extremes can be very deleterious to human well-being and this malignant effect will not appear as vicious if data is analyzed over the long term. Other factors which significantly affect effects of heat extremes on human well-being are age, sex and race. Factors, which significantly increase risk from heat exposure, are alcoholism, living on higher floors of buildings and the use of tranquilizers. Factors that minimize such risk are regular exercising, use of air-conditioners, consumption of adequate fluids and living in shaded residences (Kalkstein and Valimont, 1987). Another benign factor is acclimatization over the long term through successive short-term extreme events. Extreme cold is often almost as much an affection as heat. Very cold, dry air dehydrates nasal passages and upper respiratory tracts and creates exposure to harmful organisms and disease (Kalkstein and Valimont, 1987). Hypothermia, a condition defined by the Centers for Disease Control, 1982, as when the human core body temperature falls below C, is also another direct cause of rise in morbidity and mortality rates during winter. Factors which, either directly or indirectly, both over the long and short terms, aggravate extreme cold events, may be taken as almost the same as those that influence extreme heat events. There are a number of singularities for both extreme heat and cold events but what has been included so far in the paper is deemed to suffice for the purpose at hand. White and Hertz-Picciotto (1985) find that humidity considerably mitigates both temperature extremes. Thermoregulatory mechanisms of the human body are considerably influenced by humidity and this, in conjunction, often ameliorates or aggravates extreme temperature events. White and Hertz-Picciotto (1985) also find that variant levels of precipitation also variously affect human well-being in combination with an array of factors and other climate and weather variables. After considerable study of relevant literature the paper finds that climate and weather variables, in conjunction with a host of factors, present a large array of combinations of variables and factors that are either beneficial or deleterious to human well-being. These affections may be both direct and indirect. Another very interesting factor that is induced by climatic and weather variables is the incidence of pollen, molds and other biological entities that are airborne and, upon inhalation, initiate morbidity situations such as attacks of asthma (Kalkstein and Valimont, 1987). Climate and weather changes, induced by human activities, have the same effects on human well-being as natural phenomena. A large number of studies are being conducted at present into the implications global climate change mechanisms such as global warming may have on human well-being. Also, it needs to be mentioned that such adverse effects on well-being is not wholly physiological. Psychological effects such as sudden mood swings, aberrations from normal behavior and emotional turmoil are also induced by variations in weather components (Kalkstein and Valimont, 1987). Another factor that is taken into account when conducting studies on how human well-being is affected by climate and weather variables is lag-time. This is the difference between the extreme event and time of commencement of morbidity and/or incidence of mortality. The lag-time may be a day, a week or a month or even more – months – as is usually the case in studies conducted on climate and weather variables and human birth rates (Kalkstein and Valimont, 1987). At the very end of this literature review it is noted that while barometric pressure, as a variable that is often associated with other climate and weather variables such as large storm systems, does indirectly influence human physiology. This is confirmed (Kalkstein and Valimont, 1987, Whole Earth Forecaster, Items: 37-38, 40, 2006). There is only one instance in which atmospheric pressure was found to be the sole variable that was found responsible for affecting human mental activity (Whole Earth Forecaster, Item: 41, 2006). Again the paper notes that there is no single instance where anyone has scientifically been able to prove any relationship between barometric pressure, either alone or in tandem with other climatic and weather variables, with human fertility. This is emphasized to posit the essence of this paper. Now the paper shall investigate climate and weather variables that may affect birth rates and sperm counts. This is of specific interest to the purpose at hand. Climate and Weather Variables and Human Fertility As is the case in studies on effects of climate and weather variables on human well-being, the largest number of these involving human birth rates is on temperature variables – both summer (hot) and winter (cold). Lee (1981) found close correlations between temperature and historical populations from monthly data in England (320 Paper, Undated). Subsequent researchers have established that there are definite correlations between this variable and human fertility – which is how birth rates are made dependable on. This correlation is not unusual as it has been definite for a long time now that such variables, at extreme levels, locally affect human physiology. Fertility is a function of such physiology and high temperatures have been known to bring down sperm counts and affect sperm quality – which are dependent on hormones, substances whose secretion is known to be affected by temperature changes. There are the same usual factors such as regions, duration of the event, age, race and others already discussed earlier. There is also another significant factor that uniquely affects fertility – income (320 Paper, Undated). It has been found definitely that lower-income groups are more affected in a particular region subjected to the extreme event than higher ones. The logic is obvious – lower income groups are less capable of coping with the event. The lag time in this kind of study is usually the time of conception that is supposed to coincide with the presence or absence of extreme events and the time of birth of the babies (320 Paper, Undated). The ‘320 Paper’ is a strange undated document that is not very sophisticated but contains a mass of authentic information on weather effects on human fertility. That is why it is appreciated and utilized for this study. So, this far, after extensive review of literature available on the subject, the paper finds that there is not one single paper or research instance that either investigates or seeks to determine whether there is any association between barometric pressure and human fertility. Thus, the paper now assumes that there is very little possibility of any such association existing at all because scientists are astute persons who will immediately seize an opportunity to prove any such association if had somehow been provable scientifically. Nevertheless, on the basis of the rather verbally existing belief that there is one such association the paper decides to physically investigate it. The following methodology section describes in what manner. Methodology and Analysis The paper, quite arbitrarily chooses Tulsa in the State of Oklahoma, USA, as the exact location where the average yearly barometric pressure for the period 1990-2000 shall be extracted from the ‘National Weather Service Forecast Office, Tulsa, Oklahoma’ website together with the yearly birth rates for the period 1991-2002 from the ‘Oklahoma State Department of Health’ website. The period for the yearly birth rates is different from the barometric pressure data period because a lag-time of one year is accepted to enable better judgment. It is assumed that women conceiving under a certain pressure data period will give birth about a year later. Thus, any effect varying pressure in one year may have on conception will get reflected in the next year’s birth rates. Also, though both yearly fertility rates and total yearly number of live births are available from the same source the yearly birth rates are accepted for analysis because these are detrended. It is observed that there is significant reduction as well as increase in total population in Tulsa during this period. During the first part the population decreases while in the second it starts to increase again. This variation in total population will cause loss of homogeneity of both total number of yearly live births and yearly fertility rates from year to year. This homogeneity will not be lost in the case of yearly birth rates as changes in population from year to year is already incorporated within the yearly birth rates. Since it is first considered necessary to prove some sort of association between barometric pressure and human fertility initially no complex analytical methods are envisioned. The paper uses a simple ‘Linear correlation and regression’ test at 5% significance levels to ascertain whether any such association exists at all. Yearly average barometric pressure for Tulsa for the period 1990-2000 (Table 1) is accepted as the independent variable (x) while the yearly birth rate for the same city for the period 1991-2002 (Table 2) taking into account the ‘one year’ lag-time is accepted as the dependent variable (y). The dependency is assumed as there is yet no proof that any association exists between the two variables. As can be observed from the tables, 11 sets of variables are generated for the period under study. Table 1: Tulsa Yearly Average Barometric Pressure (1990-2000) Year Yearly Average Barometric Pressure 1990 30.045 1991 30.035 1992 29.1 1993 29.1 1994 30.01 1995 29.97 1996 29.1 1997 29.97 1998 29.95 1999 29.96 2000 30.02 Source: ‘National Weather Service Forecast Office, Tulsa, Oklahoma’ website. (The pressure data has not been rounded off as no difficulties are expected during analysis with data in this form.) Table 2: Tulsa Yearly Birth Rates (1991-2002) Period Birth Rate 1991-92 16.9 1992-93 16.4 1993-94 16 1994-95 15.4 1995-96 15.2 1996-97 15.6 1997-98 16.2 1998-99 16.4 1999-00 16.5 2000-01 16.5 2001-02 16.3 Source: ‘Oklahoma State Department of Health’ website. Results The statistical analysis was conducted at the ‘Vassar University’ website’s statistical section for simple ’Linear Correlation and Regression’. Table 3: The Correlation Coefficients and . 0.326 0.106 = The Pearson product-moment correlation coefficient. = The coefficient of Determination.(Lowry, Richard, 2006) Table 4: The Regression Coefficients. Slope Y Intercept Std. Err. of Estimate 0.408 4.0005 0.5217 Table 5: 0.95 Confidence Intervals of . Lower Limit Upper Limit 0.95 -0.34 0.774 The rest of the analytical results have been ignored. This is on the basis of the fact that the correlation coefficient is so low that the rest of the statistical results cannot make significant sense in this instance. Discussion The value of the Pearson coefficient (), though positive, is very low at 0.326 signifying that there is very little correlation between the two variables. The degree of covariance signified by the coefficient of determination () is also very low signifying that the two variables have no meaningfully associated variability between them (Vassar Inferential Statistics, Chapter 2, 2006). Thus, it can be safely stated here that the yearly average barometric pressures for Tulsa, Oklahoma, USA, have very little association with that county’s yearly birth rate for the same period. The association is so slight that it can also be safely inferred that this dissociation can be extended to other periods and other counties and states and, eventually, the whole world. The results as per table 4 signify that the Y-intercept at 4.0005 for x (barometric pressure) = 0 is absurd as no human life can be expected at that pressure in a native state (Vassar Inferential Statistics, Chapter 3, 2006). The results as per table 5 demonstrate that the confidence interval at 5% level for is so disparate that no amount of variation in the sample size will ever generate a correlation between the two variables. Conclusion In conclusion, from the results of the analysis, it is found that there is no correlation, association, at all between barometric pressure alone and birth rates, human fertility, on a global basis. Thus, the verbally transmitted belief that there is an association should be treated as a fallacious conception and those that are susceptible to it should be cautioned against any significant action on the basis of this belief. Otherwise, the paper concludes that there are many climate and weather phenomena that have significant association with human physiology, and psychology as a result, in conjunction with certain factors that either enhance or inhibit this associative effect. There is proof that variables like temperature do affect human fertility in certain degrees and there is also proof that certain human influences on the environment like environmental estrogens, artificially produced, can affect human fertility (EnviroNews, Item 4, Undated). The paper concludes that more studies be conducted on these natural and artificial variables so that their influence on human fertility can be better understand and regulatory steps, if necessary, can be taken so that human reproductive capability is not jeopardized in the future. Reference EnviroNews, Garden State EnviroNet, Items: 3 & 4, Undated. Extracted on 2nd October, 2006, from: http://www.gsenet.org/library/11gsn/1997/gs71204-.php#top Kalkstein, L.S., and K.M. Valimont, 1987, ‘Climate Effects on Human Health’. Extracted on 2nd October, 2006, from: http://www.ciesin.org/docs/001-338/001-338.html Lowry, Richard, 2006, VassarStat Website. Extracted on 4th October, 2006, from: http://faculty.vassar.edu/lowry/VassarStats.html Lunar Fertility History, 2006. Extracted on 9th October, 2006, from: http://www.menstruation.com.au/periodpages/lunarhistory.html National Weather Service Forecast Office, Tulsa, Oklahoma, (Tulsa Barometric Pressure Data Source). Extracted on 2nd October, 2006, from: http://www.srh.noaa.gov/tsa/f6current.html Oklahoma State Department of Health, Detailed Birth Statistics 1975-2004, (Tulsa Birth Rates Data Source). Extracted on 2nd October, 2006, from: http://www.health.state.ok.us/stats/vs/Birthstatistics.html 320 Paper, Undated. Extracted on 2nd October, 2006, from: http://www.mtholyoke.edu/~mirobins/320paper.doc Vassar Inferential Statistics, Chapter 3, Parts 1, 2 and 3. Extracted on 4th October, 2006, from: http://faculty.vassar.edu/lowry/webtext.html White, M.R., and I. Hertz-Picciotto, 1985, ‘Human Health: Analysis of climate related to health’, Ed. Margaret White. Extracted on 2nd October, 2006, from: http://www.ciesin.org/docs/001-235/001-235.html Whole Earth Forecaster, Weather Affects Humans, 2006, Items: 26-42. Extracted on 4th October, 2006, from: http://www.justgoodtiming.com/id45.htm Bibliography Saidi, James A., et al, Declining Sperm Counts in the United States? A Critical Review, The Journal of Urology, Vol. 161, P. 460-462, 1999. Extracted on 4th October, 2006, from: http://www.malebiologicalclock.com/docs/Declining%20Sperm%20Counts%20in%20the%20US-A%20Critical%20Review.pdf#search='James%20A%20Saidi%20Declining%20Sperm%20Counts' Schmid, Josef, The Background of Recent Fertility Trends in the Member States of the Council of Europe, Council of Europe, Population Studies No. 15, Strasbourg 1984. Extracted on 4th October, 2006, from: http://web.uni-bamberg.de/sowi/bevoelkerung/download/@index-Dateien/Council_of_Europe_1984.pdf#search='Josef%20Schmid%20The%20Background%20of%20Recent%20Fertility%20Trends' Weather Watcher, Atmospheric Pressure, 2000. Extracted on 4th October, 2006, from: http://www.boats.com/boat-articles/Weather-153/Weather+Watcher/2957.html Read More